{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('7months排.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>CNL</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>GFmilk</th>\n",
       "      <th>GFdays</th>\n",
       "      <th>ZRZ</th>\n",
       "      <th>ZDB</th>\n",
       "      <th>CNDL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Taici</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.121883</td>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.100312</td>\n",
       "      <td>0.015819</td>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.056267</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>0.280424</td>\n",
       "      <td>-0.081822</td>\n",
       "      <td>0.066566</td>\n",
       "      <td>0.057212</td>\n",
       "      <td>-0.047904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDJG</th>\n",
       "      <td>0.121883</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>0.023118</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>0.089426</td>\n",
       "      <td>0.031838</td>\n",
       "      <td>0.079993</td>\n",
       "      <td>0.073868</td>\n",
       "      <td>0.058497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRdays</th>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.346579</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>0.215548</td>\n",
       "      <td>0.383514</td>\n",
       "      <td>0.891524</td>\n",
       "      <td>0.909352</td>\n",
       "      <td>0.138192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNL</th>\n",
       "      <td>0.100312</td>\n",
       "      <td>0.023118</td>\n",
       "      <td>-0.346579</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.099501</td>\n",
       "      <td>-0.235943</td>\n",
       "      <td>-0.050199</td>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.538804</td>\n",
       "      <td>0.534154</td>\n",
       "      <td>0.507088</td>\n",
       "      <td>0.016834</td>\n",
       "      <td>-0.157010</td>\n",
       "      <td>-0.165822</td>\n",
       "      <td>0.254626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRL</th>\n",
       "      <td>0.015819</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>-0.099501</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>-0.047060</td>\n",
       "      <td>-0.030282</td>\n",
       "      <td>0.079832</td>\n",
       "      <td>0.045137</td>\n",
       "      <td>-0.015833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBL</th>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>-0.235943</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>-0.006727</td>\n",
       "      <td>0.120347</td>\n",
       "      <td>0.325674</td>\n",
       "      <td>0.338406</td>\n",
       "      <td>0.032051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tc</th>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>-0.050199</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>0.000330</td>\n",
       "      <td>-0.005849</td>\n",
       "      <td>0.049062</td>\n",
       "      <td>0.049674</td>\n",
       "      <td>-0.001881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSD</th>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>0.071629</td>\n",
       "      <td>0.043313</td>\n",
       "      <td>0.064460</td>\n",
       "      <td>0.070040</td>\n",
       "      <td>0.012148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JZmilk</th>\n",
       "      <td>-0.056267</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.538804</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>0.437067</td>\n",
       "      <td>0.332836</td>\n",
       "      <td>0.553473</td>\n",
       "      <td>0.548936</td>\n",
       "      <td>0.327275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHI</th>\n",
       "      <td>-0.056445</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>0.534154</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.436352</td>\n",
       "      <td>0.326414</td>\n",
       "      <td>0.546543</td>\n",
       "      <td>0.542943</td>\n",
       "      <td>0.320392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFmilk</th>\n",
       "      <td>0.280424</td>\n",
       "      <td>0.089426</td>\n",
       "      <td>0.215548</td>\n",
       "      <td>0.507088</td>\n",
       "      <td>-0.047060</td>\n",
       "      <td>-0.006727</td>\n",
       "      <td>0.000330</td>\n",
       "      <td>0.071629</td>\n",
       "      <td>0.437067</td>\n",
       "      <td>0.436352</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.031398</td>\n",
       "      <td>0.403882</td>\n",
       "      <td>0.396950</td>\n",
       "      <td>0.424915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFdays</th>\n",
       "      <td>-0.081822</td>\n",
       "      <td>0.031838</td>\n",
       "      <td>0.383514</td>\n",
       "      <td>0.016834</td>\n",
       "      <td>-0.030282</td>\n",
       "      <td>0.120347</td>\n",
       "      <td>-0.005849</td>\n",
       "      <td>0.043313</td>\n",
       "      <td>0.332836</td>\n",
       "      <td>0.326414</td>\n",
       "      <td>0.031398</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.330171</td>\n",
       "      <td>0.332847</td>\n",
       "      <td>-0.006832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZRZ</th>\n",
       "      <td>0.066566</td>\n",
       "      <td>0.079993</td>\n",
       "      <td>0.891524</td>\n",
       "      <td>-0.157010</td>\n",
       "      <td>0.079832</td>\n",
       "      <td>0.325674</td>\n",
       "      <td>0.049062</td>\n",
       "      <td>0.064460</td>\n",
       "      <td>0.553473</td>\n",
       "      <td>0.546543</td>\n",
       "      <td>0.403882</td>\n",
       "      <td>0.330171</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.982926</td>\n",
       "      <td>0.356444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZDB</th>\n",
       "      <td>0.057212</td>\n",
       "      <td>0.073868</td>\n",
       "      <td>0.909352</td>\n",
       "      <td>-0.165822</td>\n",
       "      <td>0.045137</td>\n",
       "      <td>0.338406</td>\n",
       "      <td>0.049674</td>\n",
       "      <td>0.070040</td>\n",
       "      <td>0.548936</td>\n",
       "      <td>0.542943</td>\n",
       "      <td>0.396950</td>\n",
       "      <td>0.332847</td>\n",
       "      <td>0.982926</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.357370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNDL</th>\n",
       "      <td>-0.047904</td>\n",
       "      <td>0.058497</td>\n",
       "      <td>0.138192</td>\n",
       "      <td>0.254626</td>\n",
       "      <td>-0.015833</td>\n",
       "      <td>0.032051</td>\n",
       "      <td>-0.001881</td>\n",
       "      <td>0.012148</td>\n",
       "      <td>0.327275</td>\n",
       "      <td>0.320392</td>\n",
       "      <td>0.424915</td>\n",
       "      <td>-0.006832</td>\n",
       "      <td>0.356444</td>\n",
       "      <td>0.357370</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Taici      CDJG    MRdays       CNL       MRL       DBL        Tc  \\\n",
       "Taici   1.000000  0.121883 -0.022526  0.100312  0.015819 -0.017366  0.062100   \n",
       "CDJG    0.121883  1.000000  0.067016  0.023118  0.005464  0.013370  0.007021   \n",
       "MRdays -0.022526  0.067016  1.000000 -0.346579  0.060074  0.351659  0.054744   \n",
       "CNL     0.100312  0.023118 -0.346579  1.000000 -0.099501 -0.235943 -0.050199   \n",
       "MRL     0.015819  0.005464  0.060074 -0.099501  1.000000  0.331627  0.050499   \n",
       "DBL    -0.017366  0.013370  0.351659 -0.235943  0.331627  1.000000  0.071991   \n",
       "Tc      0.062100  0.007021  0.054744 -0.050199  0.050499  0.071991  1.000000   \n",
       "NSD     0.011543 -0.008376  0.077701 -0.038608  0.156565  0.172289 -0.012315   \n",
       "JZmilk -0.056267  0.048543  0.462403  0.538804  0.279166  0.169783  0.004237   \n",
       "WHI    -0.056445  0.049589  0.458415  0.534154  0.283492  0.174645  0.003931   \n",
       "GFmilk  0.280424  0.089426  0.215548  0.507088 -0.047060 -0.006727  0.000330   \n",
       "GFdays -0.081822  0.031838  0.383514  0.016834 -0.030282  0.120347 -0.005849   \n",
       "ZRZ     0.066566  0.079993  0.891524 -0.157010  0.079832  0.325674  0.049062   \n",
       "ZDB     0.057212  0.073868  0.909352 -0.165822  0.045137  0.338406  0.049674   \n",
       "CNDL   -0.047904  0.058497  0.138192  0.254626 -0.015833  0.032051 -0.001881   \n",
       "\n",
       "             NSD    JZmilk       WHI    GFmilk    GFdays       ZRZ       ZDB  \\\n",
       "Taici   0.011543 -0.056267 -0.056445  0.280424 -0.081822  0.066566  0.057212   \n",
       "CDJG   -0.008376  0.048543  0.049589  0.089426  0.031838  0.079993  0.073868   \n",
       "MRdays  0.077701  0.462403  0.458415  0.215548  0.383514  0.891524  0.909352   \n",
       "CNL    -0.038608  0.538804  0.534154  0.507088  0.016834 -0.157010 -0.165822   \n",
       "MRL     0.156565  0.279166  0.283492 -0.047060 -0.030282  0.079832  0.045137   \n",
       "DBL     0.172289  0.169783  0.174645 -0.006727  0.120347  0.325674  0.338406   \n",
       "Tc     -0.012315  0.004237  0.003931  0.000330 -0.005849  0.049062  0.049674   \n",
       "NSD     1.000000  0.080992  0.113240  0.071629  0.043313  0.064460  0.070040   \n",
       "JZmilk  0.080992  1.000000  0.994654  0.437067  0.332836  0.553473  0.548936   \n",
       "WHI     0.113240  0.994654  1.000000  0.436352  0.326414  0.546543  0.542943   \n",
       "GFmilk  0.071629  0.437067  0.436352  1.000000  0.031398  0.403882  0.396950   \n",
       "GFdays  0.043313  0.332836  0.326414  0.031398  1.000000  0.330171  0.332847   \n",
       "ZRZ     0.064460  0.553473  0.546543  0.403882  0.330171  1.000000  0.982926   \n",
       "ZDB     0.070040  0.548936  0.542943  0.396950  0.332847  0.982926  1.000000   \n",
       "CNDL    0.012148  0.327275  0.320392  0.424915 -0.006832  0.356444  0.357370   \n",
       "\n",
       "            CNDL  \n",
       "Taici  -0.047904  \n",
       "CDJG    0.058497  \n",
       "MRdays  0.138192  \n",
       "CNL     0.254626  \n",
       "MRL    -0.015833  \n",
       "DBL     0.032051  \n",
       "Tc     -0.001881  \n",
       "NSD     0.012148  \n",
       "JZmilk  0.327275  \n",
       "WHI     0.320392  \n",
       "GFmilk  0.424915  \n",
       "GFdays -0.006832  \n",
       "ZRZ     0.356444  \n",
       "ZDB     0.357370  \n",
       "CNDL    1.000000  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "corr = data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 15))\n",
    "sns.heatmap(corr,annot=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "corr = data.corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 15))\n",
    "sns.heatmap(corr,annot=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = data.corr('kendall')\n",
    "plt.figure(figsize=(15, 15))\n",
    "sns.heatmap(corr,annot=True,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 随机森林特征相关性分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y=data['CNL']\n",
    "X=data[['Taici', 'CDJG', 'MRdays', 'MRL', 'DBL', 'Tc', 'NSD', 'JZmilk', 'WHI',\n",
    "       'GFmilk', 'GFdays', 'ZRZ', 'ZDB', 'CNDL']]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>GFmilk</th>\n",
       "      <th>GFdays</th>\n",
       "      <th>ZRZ</th>\n",
       "      <th>ZDB</th>\n",
       "      <th>CNDL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>345</td>\n",
       "      <td>169</td>\n",
       "      <td>3.39</td>\n",
       "      <td>3.01</td>\n",
       "      <td>67.4</td>\n",
       "      <td>10.74</td>\n",
       "      <td>37.8</td>\n",
       "      <td>89.6</td>\n",
       "      <td>45.0</td>\n",
       "      <td>17</td>\n",
       "      <td>111</td>\n",
       "      <td>99</td>\n",
       "      <td>4412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>443</td>\n",
       "      <td>254</td>\n",
       "      <td>3.24</td>\n",
       "      <td>3.12</td>\n",
       "      <td>23.6</td>\n",
       "      <td>11.53</td>\n",
       "      <td>30.3</td>\n",
       "      <td>72.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>13</td>\n",
       "      <td>79</td>\n",
       "      <td>70</td>\n",
       "      <td>4423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>300</td>\n",
       "      <td>81</td>\n",
       "      <td>3.30</td>\n",
       "      <td>2.97</td>\n",
       "      <td>22.3</td>\n",
       "      <td>11.72</td>\n",
       "      <td>21.1</td>\n",
       "      <td>52.7</td>\n",
       "      <td>25.8</td>\n",
       "      <td>81</td>\n",
       "      <td>49</td>\n",
       "      <td>41</td>\n",
       "      <td>4455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>288</td>\n",
       "      <td>275</td>\n",
       "      <td>5.47</td>\n",
       "      <td>4.59</td>\n",
       "      <td>23.5</td>\n",
       "      <td>19.43</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>1</td>\n",
       "      <td>173</td>\n",
       "      <td>152</td>\n",
       "      <td>4458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>512</td>\n",
       "      <td>269</td>\n",
       "      <td>4.18</td>\n",
       "      <td>3.34</td>\n",
       "      <td>2.9</td>\n",
       "      <td>16.77</td>\n",
       "      <td>39.5</td>\n",
       "      <td>100.3</td>\n",
       "      <td>29.2</td>\n",
       "      <td>269</td>\n",
       "      <td>161</td>\n",
       "      <td>134</td>\n",
       "      <td>4474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16507</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>251</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.17</td>\n",
       "      <td>141.9</td>\n",
       "      <td>11.63</td>\n",
       "      <td>55.6</td>\n",
       "      <td>139.2</td>\n",
       "      <td>67.1</td>\n",
       "      <td>41</td>\n",
       "      <td>499</td>\n",
       "      <td>468</td>\n",
       "      <td>16603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16508</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>214</td>\n",
       "      <td>4.51</td>\n",
       "      <td>2.78</td>\n",
       "      <td>12.1</td>\n",
       "      <td>12.38</td>\n",
       "      <td>74.3</td>\n",
       "      <td>176.3</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>568</td>\n",
       "      <td>437</td>\n",
       "      <td>16701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16509</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>286</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.50</td>\n",
       "      <td>7.1</td>\n",
       "      <td>15.46</td>\n",
       "      <td>45.9</td>\n",
       "      <td>114.6</td>\n",
       "      <td>67.1</td>\n",
       "      <td>41</td>\n",
       "      <td>549</td>\n",
       "      <td>510</td>\n",
       "      <td>16907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16510</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>239</td>\n",
       "      <td>4.53</td>\n",
       "      <td>2.85</td>\n",
       "      <td>9.2</td>\n",
       "      <td>12.98</td>\n",
       "      <td>66.8</td>\n",
       "      <td>167.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>626</td>\n",
       "      <td>473</td>\n",
       "      <td>16930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16511</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>274</td>\n",
       "      <td>3.30</td>\n",
       "      <td>3.64</td>\n",
       "      <td>138.2</td>\n",
       "      <td>14.06</td>\n",
       "      <td>57.7</td>\n",
       "      <td>144.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>688</td>\n",
       "      <td>524</td>\n",
       "      <td>17362</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Taici  CDJG  MRdays   MRL   DBL     Tc    NSD  JZmilk    WHI  GFmilk  \\\n",
       "0          6   345     169  3.39  3.01   67.4  10.74    37.8   89.6    45.0   \n",
       "1          1   443     254  3.24  3.12   23.6  11.53    30.3   72.0    45.0   \n",
       "2          1   300      81  3.30  2.97   22.3  11.72    21.1   52.7    25.8   \n",
       "3          3   288     275  5.47  4.59   23.5  19.43     3.4    8.5    25.6   \n",
       "4          5   512     269  4.18  3.34    2.9  16.77    39.5  100.3    29.2   \n",
       "...      ...   ...     ...   ...   ...    ...    ...     ...    ...     ...   \n",
       "16507      2   478     251  3.97  3.17  141.9  11.63    55.6  139.2    67.1   \n",
       "16508      2   492     214  4.51  2.78   12.1  12.38    74.3  176.3    62.0   \n",
       "16509      2   478     286  3.80  3.50    7.1  15.46    45.9  114.6    67.1   \n",
       "16510      2   492     239  4.53  2.85    9.2  12.98    66.8  167.2    62.0   \n",
       "16511      2   492     274  3.30  3.64  138.2  14.06    57.7  144.2    62.0   \n",
       "\n",
       "       GFdays  ZRZ  ZDB   CNDL  \n",
       "0          17  111   99   4412  \n",
       "1          13   79   70   4423  \n",
       "2          81   49   41   4455  \n",
       "3           1  173  152   4458  \n",
       "4         269  161  134   4474  \n",
       "...       ...  ...  ...    ...  \n",
       "16507      41  499  468  16603  \n",
       "16508      62  568  437  16701  \n",
       "16509      41  549  510  16907  \n",
       "16510      62  626  473  16930  \n",
       "16511      62  688  524  17362  \n",
       "\n",
       "[16512 rows x 14 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Taici', 'CDJG', 'MRdays', 'CNL', 'MRL', 'DBL', 'Tc', 'NSD', 'JZmilk',\n",
       "       'WHI', 'GFmilk', 'GFdays', 'ZRZ', 'ZDB', 'CNDL'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特征生成工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    |   Population Average    |             Best Individual              |\n",
      "---- ------------------------- ------------------------------------------ ----------\n",
      " Gen   Length          Fitness   Length          Fitness      OOB Fitness  Time Left\n",
      "   0    12.88         0.188032        9         0.607422         0.594545      1.60s\n",
      "   1     7.28         0.444231       30         0.708678         0.711409      0.00s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "SymbolicTransformer(function_set=['add', 'sub', 'mul', 'div', 'log', 'sqrt',\n",
       "                                  'abs', 'neg', 'max', 'min'],\n",
       "                    generations=2, max_samples=0.9, n_jobs=3,\n",
       "                    parsimony_coefficient=0.0005, random_state=0, verbose=1)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gplearn.genetic import SymbolicTransformer \n",
    "import gplearn as gp\n",
    "function_set = ['add', 'sub', 'mul', 'div', 'log', 'sqrt', 'abs', 'neg', 'max', 'min']\n",
    "# generations : 整数，可选(默认值=20)要进化的代数。\n",
    "gp1 = SymbolicTransformer(generations=2, population_size=1000,\n",
    "                         hall_of_fame=100, n_components=10,\n",
    "                         function_set=function_set,\n",
    "                         parsimony_coefficient=0.0005,\n",
    "                         max_samples=0.9, verbose=1,\n",
    "                         random_state=0, n_jobs=3)\n",
    "gp1.fit(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "gp_train_feature = gp1.transform(X)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_feature_name = [str(i)+'features ' for i in range(1, 11)]\n",
    "train_new_feature = pd.DataFrame(gp_train_feature, columns=new_feature_name, index=X.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_0 = pd.concat([X, train_new_feature], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = pd.concat([Y, x_train_0], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CNL</th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>...</th>\n",
       "      <th>1features</th>\n",
       "      <th>2features</th>\n",
       "      <th>3features</th>\n",
       "      <th>4features</th>\n",
       "      <th>5features</th>\n",
       "      <th>6features</th>\n",
       "      <th>7features</th>\n",
       "      <th>8features</th>\n",
       "      <th>9features</th>\n",
       "      <th>10features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CNL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100312</td>\n",
       "      <td>0.023118</td>\n",
       "      <td>-0.346579</td>\n",
       "      <td>-0.099501</td>\n",
       "      <td>-0.235943</td>\n",
       "      <td>-0.050199</td>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.538804</td>\n",
       "      <td>0.534154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.708985</td>\n",
       "      <td>-0.678788</td>\n",
       "      <td>0.677003</td>\n",
       "      <td>-0.652069</td>\n",
       "      <td>-0.648648</td>\n",
       "      <td>-0.647599</td>\n",
       "      <td>0.634023</td>\n",
       "      <td>0.634719</td>\n",
       "      <td>0.594413</td>\n",
       "      <td>0.584178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taici</th>\n",
       "      <td>0.100312</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.121883</td>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.015819</td>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.056267</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.083445</td>\n",
       "      <td>-0.020000</td>\n",
       "      <td>-0.100272</td>\n",
       "      <td>-0.116387</td>\n",
       "      <td>0.053519</td>\n",
       "      <td>-0.203856</td>\n",
       "      <td>0.043026</td>\n",
       "      <td>-0.090382</td>\n",
       "      <td>-0.080465</td>\n",
       "      <td>0.191892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDJG</th>\n",
       "      <td>0.023118</td>\n",
       "      <td>0.121883</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018200</td>\n",
       "      <td>-0.035725</td>\n",
       "      <td>0.012552</td>\n",
       "      <td>-0.084163</td>\n",
       "      <td>-0.035566</td>\n",
       "      <td>-0.079016</td>\n",
       "      <td>0.057405</td>\n",
       "      <td>0.009173</td>\n",
       "      <td>0.028739</td>\n",
       "      <td>0.036220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRdays</th>\n",
       "      <td>-0.346579</td>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023363</td>\n",
       "      <td>-0.229482</td>\n",
       "      <td>0.078742</td>\n",
       "      <td>-0.348489</td>\n",
       "      <td>-0.285175</td>\n",
       "      <td>-0.210292</td>\n",
       "      <td>0.323533</td>\n",
       "      <td>-0.009594</td>\n",
       "      <td>0.191923</td>\n",
       "      <td>-0.085334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRL</th>\n",
       "      <td>-0.099501</td>\n",
       "      <td>0.015819</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.316676</td>\n",
       "      <td>0.031282</td>\n",
       "      <td>0.199400</td>\n",
       "      <td>-0.158533</td>\n",
       "      <td>-0.150864</td>\n",
       "      <td>-0.037954</td>\n",
       "      <td>0.090525</td>\n",
       "      <td>0.191891</td>\n",
       "      <td>0.273616</td>\n",
       "      <td>-0.018342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBL</th>\n",
       "      <td>-0.235943</td>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>...</td>\n",
       "      <td>0.046953</td>\n",
       "      <td>-0.044177</td>\n",
       "      <td>0.023376</td>\n",
       "      <td>-0.082082</td>\n",
       "      <td>0.116393</td>\n",
       "      <td>-0.013496</td>\n",
       "      <td>0.045057</td>\n",
       "      <td>0.026936</td>\n",
       "      <td>0.081906</td>\n",
       "      <td>0.037131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tc</th>\n",
       "      <td>-0.050199</td>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.014801</td>\n",
       "      <td>0.020736</td>\n",
       "      <td>-0.028885</td>\n",
       "      <td>-0.002582</td>\n",
       "      <td>0.024739</td>\n",
       "      <td>0.014423</td>\n",
       "      <td>-0.006430</td>\n",
       "      <td>-0.022547</td>\n",
       "      <td>-0.012725</td>\n",
       "      <td>-0.015440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSD</th>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>...</td>\n",
       "      <td>0.079588</td>\n",
       "      <td>-0.032245</td>\n",
       "      <td>0.076465</td>\n",
       "      <td>0.010906</td>\n",
       "      <td>-0.057331</td>\n",
       "      <td>-0.124471</td>\n",
       "      <td>-0.179375</td>\n",
       "      <td>0.041967</td>\n",
       "      <td>0.074550</td>\n",
       "      <td>0.017427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JZmilk</th>\n",
       "      <td>0.538804</td>\n",
       "      <td>-0.056267</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.774543</td>\n",
       "      <td>-0.740917</td>\n",
       "      <td>0.767393</td>\n",
       "      <td>-0.871683</td>\n",
       "      <td>-0.864863</td>\n",
       "      <td>-0.641937</td>\n",
       "      <td>0.792900</td>\n",
       "      <td>0.660870</td>\n",
       "      <td>0.846970</td>\n",
       "      <td>0.345203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHI</th>\n",
       "      <td>0.534154</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.783254</td>\n",
       "      <td>-0.736835</td>\n",
       "      <td>0.772837</td>\n",
       "      <td>-0.870653</td>\n",
       "      <td>-0.867493</td>\n",
       "      <td>-0.642262</td>\n",
       "      <td>0.782399</td>\n",
       "      <td>0.658418</td>\n",
       "      <td>0.854459</td>\n",
       "      <td>0.342447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFmilk</th>\n",
       "      <td>0.507088</td>\n",
       "      <td>0.280424</td>\n",
       "      <td>0.089426</td>\n",
       "      <td>0.215548</td>\n",
       "      <td>-0.047060</td>\n",
       "      <td>-0.006727</td>\n",
       "      <td>0.000330</td>\n",
       "      <td>0.071629</td>\n",
       "      <td>0.437067</td>\n",
       "      <td>0.436352</td>\n",
       "      <td>...</td>\n",
       "      <td>0.290840</td>\n",
       "      <td>-0.638535</td>\n",
       "      <td>0.336506</td>\n",
       "      <td>-0.768371</td>\n",
       "      <td>-0.490242</td>\n",
       "      <td>-0.878379</td>\n",
       "      <td>0.681931</td>\n",
       "      <td>0.228431</td>\n",
       "      <td>0.324208</td>\n",
       "      <td>0.666400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFdays</th>\n",
       "      <td>0.016834</td>\n",
       "      <td>-0.081822</td>\n",
       "      <td>0.031838</td>\n",
       "      <td>0.383514</td>\n",
       "      <td>-0.030282</td>\n",
       "      <td>0.120347</td>\n",
       "      <td>-0.005849</td>\n",
       "      <td>0.043313</td>\n",
       "      <td>0.332836</td>\n",
       "      <td>0.326414</td>\n",
       "      <td>...</td>\n",
       "      <td>0.109783</td>\n",
       "      <td>-0.199935</td>\n",
       "      <td>0.192730</td>\n",
       "      <td>-0.199592</td>\n",
       "      <td>-0.269518</td>\n",
       "      <td>-0.074988</td>\n",
       "      <td>0.221235</td>\n",
       "      <td>0.097794</td>\n",
       "      <td>0.237939</td>\n",
       "      <td>-0.066680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZRZ</th>\n",
       "      <td>-0.157010</td>\n",
       "      <td>0.066566</td>\n",
       "      <td>0.079993</td>\n",
       "      <td>0.891524</td>\n",
       "      <td>0.079832</td>\n",
       "      <td>0.325674</td>\n",
       "      <td>0.049062</td>\n",
       "      <td>0.064460</td>\n",
       "      <td>0.553473</td>\n",
       "      <td>0.546543</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041322</td>\n",
       "      <td>-0.433970</td>\n",
       "      <td>0.152235</td>\n",
       "      <td>-0.524227</td>\n",
       "      <td>-0.389053</td>\n",
       "      <td>-0.408084</td>\n",
       "      <td>0.459922</td>\n",
       "      <td>0.078381</td>\n",
       "      <td>0.245390</td>\n",
       "      <td>0.251979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZDB</th>\n",
       "      <td>-0.165822</td>\n",
       "      <td>0.057212</td>\n",
       "      <td>0.073868</td>\n",
       "      <td>0.909352</td>\n",
       "      <td>0.045137</td>\n",
       "      <td>0.338406</td>\n",
       "      <td>0.049674</td>\n",
       "      <td>0.070040</td>\n",
       "      <td>0.548936</td>\n",
       "      <td>0.542943</td>\n",
       "      <td>...</td>\n",
       "      <td>0.042075</td>\n",
       "      <td>-0.433113</td>\n",
       "      <td>0.151019</td>\n",
       "      <td>-0.515287</td>\n",
       "      <td>-0.378600</td>\n",
       "      <td>-0.397994</td>\n",
       "      <td>0.450896</td>\n",
       "      <td>0.076704</td>\n",
       "      <td>0.247617</td>\n",
       "      <td>0.249890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNDL</th>\n",
       "      <td>0.254626</td>\n",
       "      <td>-0.047904</td>\n",
       "      <td>0.058497</td>\n",
       "      <td>0.138192</td>\n",
       "      <td>-0.015833</td>\n",
       "      <td>0.032051</td>\n",
       "      <td>-0.001881</td>\n",
       "      <td>0.012148</td>\n",
       "      <td>0.327275</td>\n",
       "      <td>0.320392</td>\n",
       "      <td>...</td>\n",
       "      <td>0.230597</td>\n",
       "      <td>-0.374211</td>\n",
       "      <td>0.189830</td>\n",
       "      <td>-0.456906</td>\n",
       "      <td>-0.274883</td>\n",
       "      <td>-0.428498</td>\n",
       "      <td>0.333282</td>\n",
       "      <td>0.204351</td>\n",
       "      <td>0.217478</td>\n",
       "      <td>0.461649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1features</th>\n",
       "      <td>0.708985</td>\n",
       "      <td>-0.083445</td>\n",
       "      <td>0.018200</td>\n",
       "      <td>-0.023363</td>\n",
       "      <td>0.316676</td>\n",
       "      <td>0.046953</td>\n",
       "      <td>-0.014801</td>\n",
       "      <td>0.079588</td>\n",
       "      <td>0.774543</td>\n",
       "      <td>0.783254</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.593230</td>\n",
       "      <td>0.782664</td>\n",
       "      <td>-0.689938</td>\n",
       "      <td>-0.742321</td>\n",
       "      <td>-0.519534</td>\n",
       "      <td>0.634916</td>\n",
       "      <td>0.750676</td>\n",
       "      <td>0.791938</td>\n",
       "      <td>0.270737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2features</th>\n",
       "      <td>-0.678788</td>\n",
       "      <td>-0.020000</td>\n",
       "      <td>-0.035725</td>\n",
       "      <td>-0.229482</td>\n",
       "      <td>0.031282</td>\n",
       "      <td>-0.044177</td>\n",
       "      <td>0.020736</td>\n",
       "      <td>-0.032245</td>\n",
       "      <td>-0.740917</td>\n",
       "      <td>-0.736835</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.593230</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.728726</td>\n",
       "      <td>0.795075</td>\n",
       "      <td>0.851666</td>\n",
       "      <td>0.788278</td>\n",
       "      <td>-0.892918</td>\n",
       "      <td>-0.654296</td>\n",
       "      <td>-0.600750</td>\n",
       "      <td>-0.708319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3features</th>\n",
       "      <td>0.677003</td>\n",
       "      <td>-0.100272</td>\n",
       "      <td>0.012552</td>\n",
       "      <td>0.078742</td>\n",
       "      <td>0.199400</td>\n",
       "      <td>0.023376</td>\n",
       "      <td>-0.028885</td>\n",
       "      <td>0.076465</td>\n",
       "      <td>0.767393</td>\n",
       "      <td>0.772837</td>\n",
       "      <td>...</td>\n",
       "      <td>0.782664</td>\n",
       "      <td>-0.728726</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.689365</td>\n",
       "      <td>-0.828721</td>\n",
       "      <td>-0.606653</td>\n",
       "      <td>0.734879</td>\n",
       "      <td>0.751736</td>\n",
       "      <td>0.776999</td>\n",
       "      <td>0.334597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4features</th>\n",
       "      <td>-0.652069</td>\n",
       "      <td>-0.116387</td>\n",
       "      <td>-0.084163</td>\n",
       "      <td>-0.348489</td>\n",
       "      <td>-0.158533</td>\n",
       "      <td>-0.082082</td>\n",
       "      <td>-0.002582</td>\n",
       "      <td>0.010906</td>\n",
       "      <td>-0.871683</td>\n",
       "      <td>-0.870653</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.689938</td>\n",
       "      <td>0.795075</td>\n",
       "      <td>-0.689365</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.825387</td>\n",
       "      <td>0.888808</td>\n",
       "      <td>-0.883994</td>\n",
       "      <td>-0.599409</td>\n",
       "      <td>-0.728867</td>\n",
       "      <td>-0.562344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5features</th>\n",
       "      <td>-0.648648</td>\n",
       "      <td>0.053519</td>\n",
       "      <td>-0.035566</td>\n",
       "      <td>-0.285175</td>\n",
       "      <td>-0.150864</td>\n",
       "      <td>0.116393</td>\n",
       "      <td>0.024739</td>\n",
       "      <td>-0.057331</td>\n",
       "      <td>-0.864863</td>\n",
       "      <td>-0.867493</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.742321</td>\n",
       "      <td>0.851666</td>\n",
       "      <td>-0.828721</td>\n",
       "      <td>0.825387</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.725805</td>\n",
       "      <td>-0.882678</td>\n",
       "      <td>-0.740003</td>\n",
       "      <td>-0.744495</td>\n",
       "      <td>-0.400890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6features</th>\n",
       "      <td>-0.647599</td>\n",
       "      <td>-0.203856</td>\n",
       "      <td>-0.079016</td>\n",
       "      <td>-0.210292</td>\n",
       "      <td>-0.037954</td>\n",
       "      <td>-0.013496</td>\n",
       "      <td>0.014423</td>\n",
       "      <td>-0.124471</td>\n",
       "      <td>-0.641937</td>\n",
       "      <td>-0.642262</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.519534</td>\n",
       "      <td>0.788278</td>\n",
       "      <td>-0.606653</td>\n",
       "      <td>0.888808</td>\n",
       "      <td>0.725805</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.821823</td>\n",
       "      <td>-0.523354</td>\n",
       "      <td>-0.515795</td>\n",
       "      <td>-0.651646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7features</th>\n",
       "      <td>0.634023</td>\n",
       "      <td>0.043026</td>\n",
       "      <td>0.057405</td>\n",
       "      <td>0.323533</td>\n",
       "      <td>0.090525</td>\n",
       "      <td>0.045057</td>\n",
       "      <td>-0.006430</td>\n",
       "      <td>-0.179375</td>\n",
       "      <td>0.792900</td>\n",
       "      <td>0.782399</td>\n",
       "      <td>...</td>\n",
       "      <td>0.634916</td>\n",
       "      <td>-0.892918</td>\n",
       "      <td>0.734879</td>\n",
       "      <td>-0.883994</td>\n",
       "      <td>-0.882678</td>\n",
       "      <td>-0.821823</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.673281</td>\n",
       "      <td>0.665577</td>\n",
       "      <td>0.535742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8features</th>\n",
       "      <td>0.634719</td>\n",
       "      <td>-0.090382</td>\n",
       "      <td>0.009173</td>\n",
       "      <td>-0.009594</td>\n",
       "      <td>0.191891</td>\n",
       "      <td>0.026936</td>\n",
       "      <td>-0.022547</td>\n",
       "      <td>0.041967</td>\n",
       "      <td>0.660870</td>\n",
       "      <td>0.658418</td>\n",
       "      <td>...</td>\n",
       "      <td>0.750676</td>\n",
       "      <td>-0.654296</td>\n",
       "      <td>0.751736</td>\n",
       "      <td>-0.599409</td>\n",
       "      <td>-0.740003</td>\n",
       "      <td>-0.523354</td>\n",
       "      <td>0.673281</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.616536</td>\n",
       "      <td>0.317548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9features</th>\n",
       "      <td>0.594413</td>\n",
       "      <td>-0.080465</td>\n",
       "      <td>0.028739</td>\n",
       "      <td>0.191923</td>\n",
       "      <td>0.273616</td>\n",
       "      <td>0.081906</td>\n",
       "      <td>-0.012725</td>\n",
       "      <td>0.074550</td>\n",
       "      <td>0.846970</td>\n",
       "      <td>0.854459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.791938</td>\n",
       "      <td>-0.600750</td>\n",
       "      <td>0.776999</td>\n",
       "      <td>-0.728867</td>\n",
       "      <td>-0.744495</td>\n",
       "      <td>-0.515795</td>\n",
       "      <td>0.665577</td>\n",
       "      <td>0.616536</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.269664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10features</th>\n",
       "      <td>0.584178</td>\n",
       "      <td>0.191892</td>\n",
       "      <td>0.036220</td>\n",
       "      <td>-0.085334</td>\n",
       "      <td>-0.018342</td>\n",
       "      <td>0.037131</td>\n",
       "      <td>-0.015440</td>\n",
       "      <td>0.017427</td>\n",
       "      <td>0.345203</td>\n",
       "      <td>0.342447</td>\n",
       "      <td>...</td>\n",
       "      <td>0.270737</td>\n",
       "      <td>-0.708319</td>\n",
       "      <td>0.334597</td>\n",
       "      <td>-0.562344</td>\n",
       "      <td>-0.400890</td>\n",
       "      <td>-0.651646</td>\n",
       "      <td>0.535742</td>\n",
       "      <td>0.317548</td>\n",
       "      <td>0.269664</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  CNL     Taici      CDJG    MRdays       MRL       DBL  \\\n",
       "CNL          1.000000  0.100312  0.023118 -0.346579 -0.099501 -0.235943   \n",
       "Taici        0.100312  1.000000  0.121883 -0.022526  0.015819 -0.017366   \n",
       "CDJG         0.023118  0.121883  1.000000  0.067016  0.005464  0.013370   \n",
       "MRdays      -0.346579 -0.022526  0.067016  1.000000  0.060074  0.351659   \n",
       "MRL         -0.099501  0.015819  0.005464  0.060074  1.000000  0.331627   \n",
       "DBL         -0.235943 -0.017366  0.013370  0.351659  0.331627  1.000000   \n",
       "Tc          -0.050199  0.062100  0.007021  0.054744  0.050499  0.071991   \n",
       "NSD         -0.038608  0.011543 -0.008376  0.077701  0.156565  0.172289   \n",
       "JZmilk       0.538804 -0.056267  0.048543  0.462403  0.279166  0.169783   \n",
       "WHI          0.534154 -0.056445  0.049589  0.458415  0.283492  0.174645   \n",
       "GFmilk       0.507088  0.280424  0.089426  0.215548 -0.047060 -0.006727   \n",
       "GFdays       0.016834 -0.081822  0.031838  0.383514 -0.030282  0.120347   \n",
       "ZRZ         -0.157010  0.066566  0.079993  0.891524  0.079832  0.325674   \n",
       "ZDB         -0.165822  0.057212  0.073868  0.909352  0.045137  0.338406   \n",
       "CNDL         0.254626 -0.047904  0.058497  0.138192 -0.015833  0.032051   \n",
       "1features    0.708985 -0.083445  0.018200 -0.023363  0.316676  0.046953   \n",
       "2features   -0.678788 -0.020000 -0.035725 -0.229482  0.031282 -0.044177   \n",
       "3features    0.677003 -0.100272  0.012552  0.078742  0.199400  0.023376   \n",
       "4features   -0.652069 -0.116387 -0.084163 -0.348489 -0.158533 -0.082082   \n",
       "5features   -0.648648  0.053519 -0.035566 -0.285175 -0.150864  0.116393   \n",
       "6features   -0.647599 -0.203856 -0.079016 -0.210292 -0.037954 -0.013496   \n",
       "7features    0.634023  0.043026  0.057405  0.323533  0.090525  0.045057   \n",
       "8features    0.634719 -0.090382  0.009173 -0.009594  0.191891  0.026936   \n",
       "9features    0.594413 -0.080465  0.028739  0.191923  0.273616  0.081906   \n",
       "10features   0.584178  0.191892  0.036220 -0.085334 -0.018342  0.037131   \n",
       "\n",
       "                   Tc       NSD    JZmilk       WHI  ...  1features   \\\n",
       "CNL         -0.050199 -0.038608  0.538804  0.534154  ...    0.708985   \n",
       "Taici        0.062100  0.011543 -0.056267 -0.056445  ...   -0.083445   \n",
       "CDJG         0.007021 -0.008376  0.048543  0.049589  ...    0.018200   \n",
       "MRdays       0.054744  0.077701  0.462403  0.458415  ...   -0.023363   \n",
       "MRL          0.050499  0.156565  0.279166  0.283492  ...    0.316676   \n",
       "DBL          0.071991  0.172289  0.169783  0.174645  ...    0.046953   \n",
       "Tc           1.000000 -0.012315  0.004237  0.003931  ...   -0.014801   \n",
       "NSD         -0.012315  1.000000  0.080992  0.113240  ...    0.079588   \n",
       "JZmilk       0.004237  0.080992  1.000000  0.994654  ...    0.774543   \n",
       "WHI          0.003931  0.113240  0.994654  1.000000  ...    0.783254   \n",
       "GFmilk       0.000330  0.071629  0.437067  0.436352  ...    0.290840   \n",
       "GFdays      -0.005849  0.043313  0.332836  0.326414  ...    0.109783   \n",
       "ZRZ          0.049062  0.064460  0.553473  0.546543  ...    0.041322   \n",
       "ZDB          0.049674  0.070040  0.548936  0.542943  ...    0.042075   \n",
       "CNDL        -0.001881  0.012148  0.327275  0.320392  ...    0.230597   \n",
       "1features   -0.014801  0.079588  0.774543  0.783254  ...    1.000000   \n",
       "2features    0.020736 -0.032245 -0.740917 -0.736835  ...   -0.593230   \n",
       "3features   -0.028885  0.076465  0.767393  0.772837  ...    0.782664   \n",
       "4features   -0.002582  0.010906 -0.871683 -0.870653  ...   -0.689938   \n",
       "5features    0.024739 -0.057331 -0.864863 -0.867493  ...   -0.742321   \n",
       "6features    0.014423 -0.124471 -0.641937 -0.642262  ...   -0.519534   \n",
       "7features   -0.006430 -0.179375  0.792900  0.782399  ...    0.634916   \n",
       "8features   -0.022547  0.041967  0.660870  0.658418  ...    0.750676   \n",
       "9features   -0.012725  0.074550  0.846970  0.854459  ...    0.791938   \n",
       "10features  -0.015440  0.017427  0.345203  0.342447  ...    0.270737   \n",
       "\n",
       "             2features   3features   4features   5features   6features   \\\n",
       "CNL           -0.678788    0.677003   -0.652069   -0.648648   -0.647599   \n",
       "Taici         -0.020000   -0.100272   -0.116387    0.053519   -0.203856   \n",
       "CDJG          -0.035725    0.012552   -0.084163   -0.035566   -0.079016   \n",
       "MRdays        -0.229482    0.078742   -0.348489   -0.285175   -0.210292   \n",
       "MRL            0.031282    0.199400   -0.158533   -0.150864   -0.037954   \n",
       "DBL           -0.044177    0.023376   -0.082082    0.116393   -0.013496   \n",
       "Tc             0.020736   -0.028885   -0.002582    0.024739    0.014423   \n",
       "NSD           -0.032245    0.076465    0.010906   -0.057331   -0.124471   \n",
       "JZmilk        -0.740917    0.767393   -0.871683   -0.864863   -0.641937   \n",
       "WHI           -0.736835    0.772837   -0.870653   -0.867493   -0.642262   \n",
       "GFmilk        -0.638535    0.336506   -0.768371   -0.490242   -0.878379   \n",
       "GFdays        -0.199935    0.192730   -0.199592   -0.269518   -0.074988   \n",
       "ZRZ           -0.433970    0.152235   -0.524227   -0.389053   -0.408084   \n",
       "ZDB           -0.433113    0.151019   -0.515287   -0.378600   -0.397994   \n",
       "CNDL          -0.374211    0.189830   -0.456906   -0.274883   -0.428498   \n",
       "1features     -0.593230    0.782664   -0.689938   -0.742321   -0.519534   \n",
       "2features      1.000000   -0.728726    0.795075    0.851666    0.788278   \n",
       "3features     -0.728726    1.000000   -0.689365   -0.828721   -0.606653   \n",
       "4features      0.795075   -0.689365    1.000000    0.825387    0.888808   \n",
       "5features      0.851666   -0.828721    0.825387    1.000000    0.725805   \n",
       "6features      0.788278   -0.606653    0.888808    0.725805    1.000000   \n",
       "7features     -0.892918    0.734879   -0.883994   -0.882678   -0.821823   \n",
       "8features     -0.654296    0.751736   -0.599409   -0.740003   -0.523354   \n",
       "9features     -0.600750    0.776999   -0.728867   -0.744495   -0.515795   \n",
       "10features    -0.708319    0.334597   -0.562344   -0.400890   -0.651646   \n",
       "\n",
       "             7features   8features   9features   10features   \n",
       "CNL            0.634023    0.634719    0.594413     0.584178  \n",
       "Taici          0.043026   -0.090382   -0.080465     0.191892  \n",
       "CDJG           0.057405    0.009173    0.028739     0.036220  \n",
       "MRdays         0.323533   -0.009594    0.191923    -0.085334  \n",
       "MRL            0.090525    0.191891    0.273616    -0.018342  \n",
       "DBL            0.045057    0.026936    0.081906     0.037131  \n",
       "Tc            -0.006430   -0.022547   -0.012725    -0.015440  \n",
       "NSD           -0.179375    0.041967    0.074550     0.017427  \n",
       "JZmilk         0.792900    0.660870    0.846970     0.345203  \n",
       "WHI            0.782399    0.658418    0.854459     0.342447  \n",
       "GFmilk         0.681931    0.228431    0.324208     0.666400  \n",
       "GFdays         0.221235    0.097794    0.237939    -0.066680  \n",
       "ZRZ            0.459922    0.078381    0.245390     0.251979  \n",
       "ZDB            0.450896    0.076704    0.247617     0.249890  \n",
       "CNDL           0.333282    0.204351    0.217478     0.461649  \n",
       "1features      0.634916    0.750676    0.791938     0.270737  \n",
       "2features     -0.892918   -0.654296   -0.600750    -0.708319  \n",
       "3features      0.734879    0.751736    0.776999     0.334597  \n",
       "4features     -0.883994   -0.599409   -0.728867    -0.562344  \n",
       "5features     -0.882678   -0.740003   -0.744495    -0.400890  \n",
       "6features     -0.821823   -0.523354   -0.515795    -0.651646  \n",
       "7features      1.000000    0.673281    0.665577     0.535742  \n",
       "8features      0.673281    1.000000    0.616536     0.317548  \n",
       "9features      0.665577    0.616536    1.000000     0.269664  \n",
       "10features     0.535742    0.317548    0.269664     1.000000  \n",
       "\n",
       "[25 rows x 25 columns]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CNL</th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>...</th>\n",
       "      <th>1features</th>\n",
       "      <th>2features</th>\n",
       "      <th>3features</th>\n",
       "      <th>4features</th>\n",
       "      <th>5features</th>\n",
       "      <th>6features</th>\n",
       "      <th>7features</th>\n",
       "      <th>8features</th>\n",
       "      <th>9features</th>\n",
       "      <th>10features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CNL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.176037</td>\n",
       "      <td>0.039113</td>\n",
       "      <td>-0.375147</td>\n",
       "      <td>-0.111103</td>\n",
       "      <td>-0.249814</td>\n",
       "      <td>-0.115199</td>\n",
       "      <td>-0.051031</td>\n",
       "      <td>0.493899</td>\n",
       "      <td>0.488078</td>\n",
       "      <td>...</td>\n",
       "      <td>0.768359</td>\n",
       "      <td>0.748032</td>\n",
       "      <td>0.657836</td>\n",
       "      <td>0.712889</td>\n",
       "      <td>-0.752314</td>\n",
       "      <td>0.682904</td>\n",
       "      <td>0.721592</td>\n",
       "      <td>0.650498</td>\n",
       "      <td>-0.592747</td>\n",
       "      <td>0.590888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taici</th>\n",
       "      <td>0.176037</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.119135</td>\n",
       "      <td>-0.034972</td>\n",
       "      <td>0.025159</td>\n",
       "      <td>-0.031008</td>\n",
       "      <td>0.082913</td>\n",
       "      <td>0.022747</td>\n",
       "      <td>-0.036207</td>\n",
       "      <td>-0.037690</td>\n",
       "      <td>...</td>\n",
       "      <td>0.121504</td>\n",
       "      <td>0.140970</td>\n",
       "      <td>0.331274</td>\n",
       "      <td>-0.087956</td>\n",
       "      <td>-0.003975</td>\n",
       "      <td>-0.065644</td>\n",
       "      <td>-0.097031</td>\n",
       "      <td>-0.075895</td>\n",
       "      <td>-0.086352</td>\n",
       "      <td>0.149332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDJG</th>\n",
       "      <td>0.039113</td>\n",
       "      <td>0.119135</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.045860</td>\n",
       "      <td>0.006720</td>\n",
       "      <td>0.013110</td>\n",
       "      <td>0.018937</td>\n",
       "      <td>0.008713</td>\n",
       "      <td>0.060004</td>\n",
       "      <td>0.060768</td>\n",
       "      <td>...</td>\n",
       "      <td>0.057200</td>\n",
       "      <td>0.073434</td>\n",
       "      <td>0.096491</td>\n",
       "      <td>-0.006397</td>\n",
       "      <td>0.020669</td>\n",
       "      <td>0.030930</td>\n",
       "      <td>0.011891</td>\n",
       "      <td>0.041215</td>\n",
       "      <td>-0.067450</td>\n",
       "      <td>0.086253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRdays</th>\n",
       "      <td>-0.375147</td>\n",
       "      <td>-0.034972</td>\n",
       "      <td>0.045860</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.085323</td>\n",
       "      <td>0.394159</td>\n",
       "      <td>0.189760</td>\n",
       "      <td>0.100614</td>\n",
       "      <td>0.438506</td>\n",
       "      <td>0.434125</td>\n",
       "      <td>...</td>\n",
       "      <td>0.088690</td>\n",
       "      <td>0.069147</td>\n",
       "      <td>0.079432</td>\n",
       "      <td>-0.335446</td>\n",
       "      <td>0.799657</td>\n",
       "      <td>-0.051971</td>\n",
       "      <td>-0.167728</td>\n",
       "      <td>0.155541</td>\n",
       "      <td>-0.272798</td>\n",
       "      <td>0.333057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRL</th>\n",
       "      <td>-0.111103</td>\n",
       "      <td>0.025159</td>\n",
       "      <td>0.006720</td>\n",
       "      <td>0.085323</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.344518</td>\n",
       "      <td>0.095383</td>\n",
       "      <td>0.148472</td>\n",
       "      <td>0.292637</td>\n",
       "      <td>0.299698</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013373</td>\n",
       "      <td>0.225304</td>\n",
       "      <td>-0.003315</td>\n",
       "      <td>0.224728</td>\n",
       "      <td>0.062255</td>\n",
       "      <td>0.325603</td>\n",
       "      <td>0.290364</td>\n",
       "      <td>0.315255</td>\n",
       "      <td>0.393127</td>\n",
       "      <td>0.128748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBL</th>\n",
       "      <td>-0.249814</td>\n",
       "      <td>-0.031008</td>\n",
       "      <td>0.013110</td>\n",
       "      <td>0.394159</td>\n",
       "      <td>0.344518</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.116960</td>\n",
       "      <td>0.180806</td>\n",
       "      <td>0.198411</td>\n",
       "      <td>0.203277</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022326</td>\n",
       "      <td>0.030020</td>\n",
       "      <td>-0.050008</td>\n",
       "      <td>-0.096964</td>\n",
       "      <td>0.341066</td>\n",
       "      <td>0.047639</td>\n",
       "      <td>-0.028736</td>\n",
       "      <td>0.092651</td>\n",
       "      <td>0.077938</td>\n",
       "      <td>0.061640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tc</th>\n",
       "      <td>-0.115199</td>\n",
       "      <td>0.082913</td>\n",
       "      <td>0.018937</td>\n",
       "      <td>0.189760</td>\n",
       "      <td>0.095383</td>\n",
       "      <td>0.116960</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.094497</td>\n",
       "      <td>0.065160</td>\n",
       "      <td>0.066818</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.024773</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>-0.002064</td>\n",
       "      <td>-0.098081</td>\n",
       "      <td>0.172869</td>\n",
       "      <td>-0.022360</td>\n",
       "      <td>-0.074765</td>\n",
       "      <td>-0.001600</td>\n",
       "      <td>0.006507</td>\n",
       "      <td>0.082935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSD</th>\n",
       "      <td>-0.051031</td>\n",
       "      <td>0.022747</td>\n",
       "      <td>0.008713</td>\n",
       "      <td>0.100614</td>\n",
       "      <td>0.148472</td>\n",
       "      <td>0.180806</td>\n",
       "      <td>-0.094497</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.078836</td>\n",
       "      <td>0.113263</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043540</td>\n",
       "      <td>0.105500</td>\n",
       "      <td>0.081502</td>\n",
       "      <td>0.198963</td>\n",
       "      <td>0.096077</td>\n",
       "      <td>0.068141</td>\n",
       "      <td>0.166657</td>\n",
       "      <td>0.115946</td>\n",
       "      <td>0.031315</td>\n",
       "      <td>-0.231493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JZmilk</th>\n",
       "      <td>0.493899</td>\n",
       "      <td>-0.036207</td>\n",
       "      <td>0.060004</td>\n",
       "      <td>0.438506</td>\n",
       "      <td>0.292637</td>\n",
       "      <td>0.198411</td>\n",
       "      <td>0.065160</td>\n",
       "      <td>0.078836</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.992960</td>\n",
       "      <td>...</td>\n",
       "      <td>0.784010</td>\n",
       "      <td>0.822735</td>\n",
       "      <td>0.588993</td>\n",
       "      <td>0.492278</td>\n",
       "      <td>-0.050693</td>\n",
       "      <td>0.772936</td>\n",
       "      <td>0.670214</td>\n",
       "      <td>0.914786</td>\n",
       "      <td>-0.635570</td>\n",
       "      <td>0.854487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHI</th>\n",
       "      <td>0.488078</td>\n",
       "      <td>-0.037690</td>\n",
       "      <td>0.060768</td>\n",
       "      <td>0.434125</td>\n",
       "      <td>0.299698</td>\n",
       "      <td>0.203277</td>\n",
       "      <td>0.066818</td>\n",
       "      <td>0.113263</td>\n",
       "      <td>0.992960</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.782863</td>\n",
       "      <td>0.830684</td>\n",
       "      <td>0.589794</td>\n",
       "      <td>0.512184</td>\n",
       "      <td>-0.050348</td>\n",
       "      <td>0.785085</td>\n",
       "      <td>0.688620</td>\n",
       "      <td>0.926844</td>\n",
       "      <td>-0.627173</td>\n",
       "      <td>0.835777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFmilk</th>\n",
       "      <td>0.466738</td>\n",
       "      <td>0.441477</td>\n",
       "      <td>0.115829</td>\n",
       "      <td>0.187836</td>\n",
       "      <td>-0.030917</td>\n",
       "      <td>-0.008619</td>\n",
       "      <td>0.037286</td>\n",
       "      <td>0.079775</td>\n",
       "      <td>0.407368</td>\n",
       "      <td>0.406775</td>\n",
       "      <td>...</td>\n",
       "      <td>0.590008</td>\n",
       "      <td>0.627615</td>\n",
       "      <td>0.849650</td>\n",
       "      <td>0.147717</td>\n",
       "      <td>-0.058035</td>\n",
       "      <td>0.265046</td>\n",
       "      <td>0.217709</td>\n",
       "      <td>0.334386</td>\n",
       "      <td>-0.571454</td>\n",
       "      <td>0.662687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFdays</th>\n",
       "      <td>0.026414</td>\n",
       "      <td>-0.130104</td>\n",
       "      <td>0.030820</td>\n",
       "      <td>0.425547</td>\n",
       "      <td>-0.025575</td>\n",
       "      <td>0.120181</td>\n",
       "      <td>0.019827</td>\n",
       "      <td>0.057532</td>\n",
       "      <td>0.355417</td>\n",
       "      <td>0.350870</td>\n",
       "      <td>...</td>\n",
       "      <td>0.167926</td>\n",
       "      <td>0.106244</td>\n",
       "      <td>0.035249</td>\n",
       "      <td>-0.027961</td>\n",
       "      <td>0.279617</td>\n",
       "      <td>0.096886</td>\n",
       "      <td>0.144110</td>\n",
       "      <td>0.273541</td>\n",
       "      <td>-0.279826</td>\n",
       "      <td>0.227789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZRZ</th>\n",
       "      <td>-0.176660</td>\n",
       "      <td>0.086635</td>\n",
       "      <td>0.063407</td>\n",
       "      <td>0.901475</td>\n",
       "      <td>0.103566</td>\n",
       "      <td>0.361708</td>\n",
       "      <td>0.175812</td>\n",
       "      <td>0.091191</td>\n",
       "      <td>0.548131</td>\n",
       "      <td>0.540749</td>\n",
       "      <td>...</td>\n",
       "      <td>0.344184</td>\n",
       "      <td>0.223130</td>\n",
       "      <td>0.278187</td>\n",
       "      <td>-0.298570</td>\n",
       "      <td>0.641559</td>\n",
       "      <td>0.026605</td>\n",
       "      <td>-0.126579</td>\n",
       "      <td>0.236910</td>\n",
       "      <td>-0.406142</td>\n",
       "      <td>0.501964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZDB</th>\n",
       "      <td>-0.186032</td>\n",
       "      <td>0.074026</td>\n",
       "      <td>0.057428</td>\n",
       "      <td>0.917549</td>\n",
       "      <td>0.070782</td>\n",
       "      <td>0.377293</td>\n",
       "      <td>0.175712</td>\n",
       "      <td>0.097770</td>\n",
       "      <td>0.539623</td>\n",
       "      <td>0.533152</td>\n",
       "      <td>...</td>\n",
       "      <td>0.348336</td>\n",
       "      <td>0.218757</td>\n",
       "      <td>0.274601</td>\n",
       "      <td>-0.290881</td>\n",
       "      <td>0.654551</td>\n",
       "      <td>0.024809</td>\n",
       "      <td>-0.120970</td>\n",
       "      <td>0.234893</td>\n",
       "      <td>-0.419738</td>\n",
       "      <td>0.491982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNDL</th>\n",
       "      <td>0.252641</td>\n",
       "      <td>0.018731</td>\n",
       "      <td>0.063538</td>\n",
       "      <td>0.143839</td>\n",
       "      <td>-0.021051</td>\n",
       "      <td>0.039798</td>\n",
       "      <td>0.005458</td>\n",
       "      <td>0.019510</td>\n",
       "      <td>0.363127</td>\n",
       "      <td>0.355240</td>\n",
       "      <td>...</td>\n",
       "      <td>0.484745</td>\n",
       "      <td>0.408194</td>\n",
       "      <td>0.443865</td>\n",
       "      <td>0.114649</td>\n",
       "      <td>-0.093699</td>\n",
       "      <td>0.251558</td>\n",
       "      <td>0.118491</td>\n",
       "      <td>0.258754</td>\n",
       "      <td>-0.393625</td>\n",
       "      <td>0.451659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1features</th>\n",
       "      <td>0.768359</td>\n",
       "      <td>0.121504</td>\n",
       "      <td>0.057200</td>\n",
       "      <td>0.088690</td>\n",
       "      <td>0.013373</td>\n",
       "      <td>0.022326</td>\n",
       "      <td>-0.024773</td>\n",
       "      <td>0.043540</td>\n",
       "      <td>0.784010</td>\n",
       "      <td>0.782863</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.832442</td>\n",
       "      <td>0.759919</td>\n",
       "      <td>0.506104</td>\n",
       "      <td>-0.368061</td>\n",
       "      <td>0.683352</td>\n",
       "      <td>0.618906</td>\n",
       "      <td>0.772718</td>\n",
       "      <td>-0.742197</td>\n",
       "      <td>0.810034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2features</th>\n",
       "      <td>0.748032</td>\n",
       "      <td>0.140970</td>\n",
       "      <td>0.073434</td>\n",
       "      <td>0.069147</td>\n",
       "      <td>0.225304</td>\n",
       "      <td>0.030020</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>0.105500</td>\n",
       "      <td>0.822735</td>\n",
       "      <td>0.830684</td>\n",
       "      <td>...</td>\n",
       "      <td>0.832442</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.810305</td>\n",
       "      <td>0.710706</td>\n",
       "      <td>-0.398091</td>\n",
       "      <td>0.874705</td>\n",
       "      <td>0.775697</td>\n",
       "      <td>0.870836</td>\n",
       "      <td>-0.635116</td>\n",
       "      <td>0.828227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3features</th>\n",
       "      <td>0.657836</td>\n",
       "      <td>0.331274</td>\n",
       "      <td>0.096491</td>\n",
       "      <td>0.079432</td>\n",
       "      <td>-0.003315</td>\n",
       "      <td>-0.050008</td>\n",
       "      <td>-0.002064</td>\n",
       "      <td>0.081502</td>\n",
       "      <td>0.588993</td>\n",
       "      <td>0.589794</td>\n",
       "      <td>...</td>\n",
       "      <td>0.759919</td>\n",
       "      <td>0.810305</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.376220</td>\n",
       "      <td>-0.264362</td>\n",
       "      <td>0.487298</td>\n",
       "      <td>0.429488</td>\n",
       "      <td>0.557863</td>\n",
       "      <td>-0.710597</td>\n",
       "      <td>0.768273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4features</th>\n",
       "      <td>0.712889</td>\n",
       "      <td>-0.087956</td>\n",
       "      <td>-0.006397</td>\n",
       "      <td>-0.335446</td>\n",
       "      <td>0.224728</td>\n",
       "      <td>-0.096964</td>\n",
       "      <td>-0.098081</td>\n",
       "      <td>0.198963</td>\n",
       "      <td>0.492278</td>\n",
       "      <td>0.512184</td>\n",
       "      <td>...</td>\n",
       "      <td>0.506104</td>\n",
       "      <td>0.710706</td>\n",
       "      <td>0.376220</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.689350</td>\n",
       "      <td>0.853746</td>\n",
       "      <td>0.887571</td>\n",
       "      <td>0.735304</td>\n",
       "      <td>-0.230403</td>\n",
       "      <td>0.355225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5features</th>\n",
       "      <td>-0.752314</td>\n",
       "      <td>-0.003975</td>\n",
       "      <td>0.020669</td>\n",
       "      <td>0.799657</td>\n",
       "      <td>0.062255</td>\n",
       "      <td>0.341066</td>\n",
       "      <td>0.172869</td>\n",
       "      <td>0.096077</td>\n",
       "      <td>-0.050693</td>\n",
       "      <td>-0.050348</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.368061</td>\n",
       "      <td>-0.398091</td>\n",
       "      <td>-0.264362</td>\n",
       "      <td>-0.689350</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.510826</td>\n",
       "      <td>-0.551960</td>\n",
       "      <td>-0.310446</td>\n",
       "      <td>0.133792</td>\n",
       "      <td>-0.127493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6features</th>\n",
       "      <td>0.682904</td>\n",
       "      <td>-0.065644</td>\n",
       "      <td>0.030930</td>\n",
       "      <td>-0.051971</td>\n",
       "      <td>0.325603</td>\n",
       "      <td>0.047639</td>\n",
       "      <td>-0.022360</td>\n",
       "      <td>0.068141</td>\n",
       "      <td>0.772936</td>\n",
       "      <td>0.785085</td>\n",
       "      <td>...</td>\n",
       "      <td>0.683352</td>\n",
       "      <td>0.874705</td>\n",
       "      <td>0.487298</td>\n",
       "      <td>0.853746</td>\n",
       "      <td>-0.510826</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.889805</td>\n",
       "      <td>0.906436</td>\n",
       "      <td>-0.409324</td>\n",
       "      <td>0.645596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7features</th>\n",
       "      <td>0.721592</td>\n",
       "      <td>-0.097031</td>\n",
       "      <td>0.011891</td>\n",
       "      <td>-0.167728</td>\n",
       "      <td>0.290364</td>\n",
       "      <td>-0.028736</td>\n",
       "      <td>-0.074765</td>\n",
       "      <td>0.166657</td>\n",
       "      <td>0.670214</td>\n",
       "      <td>0.688620</td>\n",
       "      <td>...</td>\n",
       "      <td>0.618906</td>\n",
       "      <td>0.775697</td>\n",
       "      <td>0.429488</td>\n",
       "      <td>0.887571</td>\n",
       "      <td>-0.551960</td>\n",
       "      <td>0.889805</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.896710</td>\n",
       "      <td>-0.356631</td>\n",
       "      <td>0.514102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8features</th>\n",
       "      <td>0.650498</td>\n",
       "      <td>-0.075895</td>\n",
       "      <td>0.041215</td>\n",
       "      <td>0.155541</td>\n",
       "      <td>0.315255</td>\n",
       "      <td>0.092651</td>\n",
       "      <td>-0.001600</td>\n",
       "      <td>0.115946</td>\n",
       "      <td>0.914786</td>\n",
       "      <td>0.926844</td>\n",
       "      <td>...</td>\n",
       "      <td>0.772718</td>\n",
       "      <td>0.870836</td>\n",
       "      <td>0.557863</td>\n",
       "      <td>0.735304</td>\n",
       "      <td>-0.310446</td>\n",
       "      <td>0.906436</td>\n",
       "      <td>0.896710</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.545055</td>\n",
       "      <td>0.750601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9features</th>\n",
       "      <td>-0.592747</td>\n",
       "      <td>-0.086352</td>\n",
       "      <td>-0.067450</td>\n",
       "      <td>-0.272798</td>\n",
       "      <td>0.393127</td>\n",
       "      <td>0.077938</td>\n",
       "      <td>0.006507</td>\n",
       "      <td>0.031315</td>\n",
       "      <td>-0.635570</td>\n",
       "      <td>-0.627173</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.742197</td>\n",
       "      <td>-0.635116</td>\n",
       "      <td>-0.710597</td>\n",
       "      <td>-0.230403</td>\n",
       "      <td>0.133792</td>\n",
       "      <td>-0.409324</td>\n",
       "      <td>-0.356631</td>\n",
       "      <td>-0.545055</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.722595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10features</th>\n",
       "      <td>0.590888</td>\n",
       "      <td>0.149332</td>\n",
       "      <td>0.086253</td>\n",
       "      <td>0.333057</td>\n",
       "      <td>0.128748</td>\n",
       "      <td>0.061640</td>\n",
       "      <td>0.082935</td>\n",
       "      <td>-0.231493</td>\n",
       "      <td>0.854487</td>\n",
       "      <td>0.835777</td>\n",
       "      <td>...</td>\n",
       "      <td>0.810034</td>\n",
       "      <td>0.828227</td>\n",
       "      <td>0.768273</td>\n",
       "      <td>0.355225</td>\n",
       "      <td>-0.127493</td>\n",
       "      <td>0.645596</td>\n",
       "      <td>0.514102</td>\n",
       "      <td>0.750601</td>\n",
       "      <td>-0.722595</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  CNL     Taici      CDJG    MRdays       MRL       DBL  \\\n",
       "CNL          1.000000  0.176037  0.039113 -0.375147 -0.111103 -0.249814   \n",
       "Taici        0.176037  1.000000  0.119135 -0.034972  0.025159 -0.031008   \n",
       "CDJG         0.039113  0.119135  1.000000  0.045860  0.006720  0.013110   \n",
       "MRdays      -0.375147 -0.034972  0.045860  1.000000  0.085323  0.394159   \n",
       "MRL         -0.111103  0.025159  0.006720  0.085323  1.000000  0.344518   \n",
       "DBL         -0.249814 -0.031008  0.013110  0.394159  0.344518  1.000000   \n",
       "Tc          -0.115199  0.082913  0.018937  0.189760  0.095383  0.116960   \n",
       "NSD         -0.051031  0.022747  0.008713  0.100614  0.148472  0.180806   \n",
       "JZmilk       0.493899 -0.036207  0.060004  0.438506  0.292637  0.198411   \n",
       "WHI          0.488078 -0.037690  0.060768  0.434125  0.299698  0.203277   \n",
       "GFmilk       0.466738  0.441477  0.115829  0.187836 -0.030917 -0.008619   \n",
       "GFdays       0.026414 -0.130104  0.030820  0.425547 -0.025575  0.120181   \n",
       "ZRZ         -0.176660  0.086635  0.063407  0.901475  0.103566  0.361708   \n",
       "ZDB         -0.186032  0.074026  0.057428  0.917549  0.070782  0.377293   \n",
       "CNDL         0.252641  0.018731  0.063538  0.143839 -0.021051  0.039798   \n",
       "1features    0.768359  0.121504  0.057200  0.088690  0.013373  0.022326   \n",
       "2features    0.748032  0.140970  0.073434  0.069147  0.225304  0.030020   \n",
       "3features    0.657836  0.331274  0.096491  0.079432 -0.003315 -0.050008   \n",
       "4features    0.712889 -0.087956 -0.006397 -0.335446  0.224728 -0.096964   \n",
       "5features   -0.752314 -0.003975  0.020669  0.799657  0.062255  0.341066   \n",
       "6features    0.682904 -0.065644  0.030930 -0.051971  0.325603  0.047639   \n",
       "7features    0.721592 -0.097031  0.011891 -0.167728  0.290364 -0.028736   \n",
       "8features    0.650498 -0.075895  0.041215  0.155541  0.315255  0.092651   \n",
       "9features   -0.592747 -0.086352 -0.067450 -0.272798  0.393127  0.077938   \n",
       "10features   0.590888  0.149332  0.086253  0.333057  0.128748  0.061640   \n",
       "\n",
       "                   Tc       NSD    JZmilk       WHI  ...  1features   \\\n",
       "CNL         -0.115199 -0.051031  0.493899  0.488078  ...    0.768359   \n",
       "Taici        0.082913  0.022747 -0.036207 -0.037690  ...    0.121504   \n",
       "CDJG         0.018937  0.008713  0.060004  0.060768  ...    0.057200   \n",
       "MRdays       0.189760  0.100614  0.438506  0.434125  ...    0.088690   \n",
       "MRL          0.095383  0.148472  0.292637  0.299698  ...    0.013373   \n",
       "DBL          0.116960  0.180806  0.198411  0.203277  ...    0.022326   \n",
       "Tc           1.000000 -0.094497  0.065160  0.066818  ...   -0.024773   \n",
       "NSD         -0.094497  1.000000  0.078836  0.113263  ...    0.043540   \n",
       "JZmilk       0.065160  0.078836  1.000000  0.992960  ...    0.784010   \n",
       "WHI          0.066818  0.113263  0.992960  1.000000  ...    0.782863   \n",
       "GFmilk       0.037286  0.079775  0.407368  0.406775  ...    0.590008   \n",
       "GFdays       0.019827  0.057532  0.355417  0.350870  ...    0.167926   \n",
       "ZRZ          0.175812  0.091191  0.548131  0.540749  ...    0.344184   \n",
       "ZDB          0.175712  0.097770  0.539623  0.533152  ...    0.348336   \n",
       "CNDL         0.005458  0.019510  0.363127  0.355240  ...    0.484745   \n",
       "1features   -0.024773  0.043540  0.784010  0.782863  ...    1.000000   \n",
       "2features   -0.000013  0.105500  0.822735  0.830684  ...    0.832442   \n",
       "3features   -0.002064  0.081502  0.588993  0.589794  ...    0.759919   \n",
       "4features   -0.098081  0.198963  0.492278  0.512184  ...    0.506104   \n",
       "5features    0.172869  0.096077 -0.050693 -0.050348  ...   -0.368061   \n",
       "6features   -0.022360  0.068141  0.772936  0.785085  ...    0.683352   \n",
       "7features   -0.074765  0.166657  0.670214  0.688620  ...    0.618906   \n",
       "8features   -0.001600  0.115946  0.914786  0.926844  ...    0.772718   \n",
       "9features    0.006507  0.031315 -0.635570 -0.627173  ...   -0.742197   \n",
       "10features   0.082935 -0.231493  0.854487  0.835777  ...    0.810034   \n",
       "\n",
       "             2features   3features   4features   5features   6features   \\\n",
       "CNL            0.748032    0.657836    0.712889   -0.752314    0.682904   \n",
       "Taici          0.140970    0.331274   -0.087956   -0.003975   -0.065644   \n",
       "CDJG           0.073434    0.096491   -0.006397    0.020669    0.030930   \n",
       "MRdays         0.069147    0.079432   -0.335446    0.799657   -0.051971   \n",
       "MRL            0.225304   -0.003315    0.224728    0.062255    0.325603   \n",
       "DBL            0.030020   -0.050008   -0.096964    0.341066    0.047639   \n",
       "Tc            -0.000013   -0.002064   -0.098081    0.172869   -0.022360   \n",
       "NSD            0.105500    0.081502    0.198963    0.096077    0.068141   \n",
       "JZmilk         0.822735    0.588993    0.492278   -0.050693    0.772936   \n",
       "WHI            0.830684    0.589794    0.512184   -0.050348    0.785085   \n",
       "GFmilk         0.627615    0.849650    0.147717   -0.058035    0.265046   \n",
       "GFdays         0.106244    0.035249   -0.027961    0.279617    0.096886   \n",
       "ZRZ            0.223130    0.278187   -0.298570    0.641559    0.026605   \n",
       "ZDB            0.218757    0.274601   -0.290881    0.654551    0.024809   \n",
       "CNDL           0.408194    0.443865    0.114649   -0.093699    0.251558   \n",
       "1features      0.832442    0.759919    0.506104   -0.368061    0.683352   \n",
       "2features      1.000000    0.810305    0.710706   -0.398091    0.874705   \n",
       "3features      0.810305    1.000000    0.376220   -0.264362    0.487298   \n",
       "4features      0.710706    0.376220    1.000000   -0.689350    0.853746   \n",
       "5features     -0.398091   -0.264362   -0.689350    1.000000   -0.510826   \n",
       "6features      0.874705    0.487298    0.853746   -0.510826    1.000000   \n",
       "7features      0.775697    0.429488    0.887571   -0.551960    0.889805   \n",
       "8features      0.870836    0.557863    0.735304   -0.310446    0.906436   \n",
       "9features     -0.635116   -0.710597   -0.230403    0.133792   -0.409324   \n",
       "10features     0.828227    0.768273    0.355225   -0.127493    0.645596   \n",
       "\n",
       "             7features   8features   9features   10features   \n",
       "CNL            0.721592    0.650498   -0.592747     0.590888  \n",
       "Taici         -0.097031   -0.075895   -0.086352     0.149332  \n",
       "CDJG           0.011891    0.041215   -0.067450     0.086253  \n",
       "MRdays        -0.167728    0.155541   -0.272798     0.333057  \n",
       "MRL            0.290364    0.315255    0.393127     0.128748  \n",
       "DBL           -0.028736    0.092651    0.077938     0.061640  \n",
       "Tc            -0.074765   -0.001600    0.006507     0.082935  \n",
       "NSD            0.166657    0.115946    0.031315    -0.231493  \n",
       "JZmilk         0.670214    0.914786   -0.635570     0.854487  \n",
       "WHI            0.688620    0.926844   -0.627173     0.835777  \n",
       "GFmilk         0.217709    0.334386   -0.571454     0.662687  \n",
       "GFdays         0.144110    0.273541   -0.279826     0.227789  \n",
       "ZRZ           -0.126579    0.236910   -0.406142     0.501964  \n",
       "ZDB           -0.120970    0.234893   -0.419738     0.491982  \n",
       "CNDL           0.118491    0.258754   -0.393625     0.451659  \n",
       "1features      0.618906    0.772718   -0.742197     0.810034  \n",
       "2features      0.775697    0.870836   -0.635116     0.828227  \n",
       "3features      0.429488    0.557863   -0.710597     0.768273  \n",
       "4features      0.887571    0.735304   -0.230403     0.355225  \n",
       "5features     -0.551960   -0.310446    0.133792    -0.127493  \n",
       "6features      0.889805    0.906436   -0.409324     0.645596  \n",
       "7features      1.000000    0.896710   -0.356631     0.514102  \n",
       "8features      0.896710    1.000000   -0.545055     0.750601  \n",
       "9features     -0.356631   -0.545055    1.000000    -0.722595  \n",
       "10features     0.514102    0.750601   -0.722595     1.000000  \n",
       "\n",
       "[25 rows x 25 columns]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['CNL', 'Taici', 'CDJG', 'MRdays', 'MRL', 'DBL', 'Tc', 'NSD', 'JZmilk',\n",
       "       'WHI', 'GFmilk', 'GFdays', 'ZRZ', 'ZDB', 'CNDL', '1features ',\n",
       "       '2features ', '3features ', '4features ', '5features ', '6features ',\n",
       "       '7features ', '8features ', '9features ', '10features '],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>GFmilk</th>\n",
       "      <th>GFdays</th>\n",
       "      <th>ZRZ</th>\n",
       "      <th>ZDB</th>\n",
       "      <th>CNDL</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>345</td>\n",
       "      <td>169</td>\n",
       "      <td>3.39</td>\n",
       "      <td>3.01</td>\n",
       "      <td>67.4</td>\n",
       "      <td>10.74</td>\n",
       "      <td>37.8</td>\n",
       "      <td>89.6</td>\n",
       "      <td>45.0</td>\n",
       "      <td>17</td>\n",
       "      <td>111</td>\n",
       "      <td>99</td>\n",
       "      <td>4412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>443</td>\n",
       "      <td>254</td>\n",
       "      <td>3.24</td>\n",
       "      <td>3.12</td>\n",
       "      <td>23.6</td>\n",
       "      <td>11.53</td>\n",
       "      <td>30.3</td>\n",
       "      <td>72.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>13</td>\n",
       "      <td>79</td>\n",
       "      <td>70</td>\n",
       "      <td>4423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>300</td>\n",
       "      <td>81</td>\n",
       "      <td>3.30</td>\n",
       "      <td>2.97</td>\n",
       "      <td>22.3</td>\n",
       "      <td>11.72</td>\n",
       "      <td>21.1</td>\n",
       "      <td>52.7</td>\n",
       "      <td>25.8</td>\n",
       "      <td>81</td>\n",
       "      <td>49</td>\n",
       "      <td>41</td>\n",
       "      <td>4455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>288</td>\n",
       "      <td>275</td>\n",
       "      <td>5.47</td>\n",
       "      <td>4.59</td>\n",
       "      <td>23.5</td>\n",
       "      <td>19.43</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>1</td>\n",
       "      <td>173</td>\n",
       "      <td>152</td>\n",
       "      <td>4458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>512</td>\n",
       "      <td>269</td>\n",
       "      <td>4.18</td>\n",
       "      <td>3.34</td>\n",
       "      <td>2.9</td>\n",
       "      <td>16.77</td>\n",
       "      <td>39.5</td>\n",
       "      <td>100.3</td>\n",
       "      <td>29.2</td>\n",
       "      <td>269</td>\n",
       "      <td>161</td>\n",
       "      <td>134</td>\n",
       "      <td>4474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16507</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>251</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.17</td>\n",
       "      <td>141.9</td>\n",
       "      <td>11.63</td>\n",
       "      <td>55.6</td>\n",
       "      <td>139.2</td>\n",
       "      <td>67.1</td>\n",
       "      <td>41</td>\n",
       "      <td>499</td>\n",
       "      <td>468</td>\n",
       "      <td>16603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16508</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>214</td>\n",
       "      <td>4.51</td>\n",
       "      <td>2.78</td>\n",
       "      <td>12.1</td>\n",
       "      <td>12.38</td>\n",
       "      <td>74.3</td>\n",
       "      <td>176.3</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>568</td>\n",
       "      <td>437</td>\n",
       "      <td>16701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16509</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>286</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.50</td>\n",
       "      <td>7.1</td>\n",
       "      <td>15.46</td>\n",
       "      <td>45.9</td>\n",
       "      <td>114.6</td>\n",
       "      <td>67.1</td>\n",
       "      <td>41</td>\n",
       "      <td>549</td>\n",
       "      <td>510</td>\n",
       "      <td>16907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16510</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>239</td>\n",
       "      <td>4.53</td>\n",
       "      <td>2.85</td>\n",
       "      <td>9.2</td>\n",
       "      <td>12.98</td>\n",
       "      <td>66.8</td>\n",
       "      <td>167.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>626</td>\n",
       "      <td>473</td>\n",
       "      <td>16930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16511</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>274</td>\n",
       "      <td>3.30</td>\n",
       "      <td>3.64</td>\n",
       "      <td>138.2</td>\n",
       "      <td>14.06</td>\n",
       "      <td>57.7</td>\n",
       "      <td>144.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>62</td>\n",
       "      <td>688</td>\n",
       "      <td>524</td>\n",
       "      <td>17362</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Taici  CDJG  MRdays   MRL   DBL     Tc    NSD  JZmilk    WHI  GFmilk  \\\n",
       "0          6   345     169  3.39  3.01   67.4  10.74    37.8   89.6    45.0   \n",
       "1          1   443     254  3.24  3.12   23.6  11.53    30.3   72.0    45.0   \n",
       "2          1   300      81  3.30  2.97   22.3  11.72    21.1   52.7    25.8   \n",
       "3          3   288     275  5.47  4.59   23.5  19.43     3.4    8.5    25.6   \n",
       "4          5   512     269  4.18  3.34    2.9  16.77    39.5  100.3    29.2   \n",
       "...      ...   ...     ...   ...   ...    ...    ...     ...    ...     ...   \n",
       "16507      2   478     251  3.97  3.17  141.9  11.63    55.6  139.2    67.1   \n",
       "16508      2   492     214  4.51  2.78   12.1  12.38    74.3  176.3    62.0   \n",
       "16509      2   478     286  3.80  3.50    7.1  15.46    45.9  114.6    67.1   \n",
       "16510      2   492     239  4.53  2.85    9.2  12.98    66.8  167.2    62.0   \n",
       "16511      2   492     274  3.30  3.64  138.2  14.06    57.7  144.2    62.0   \n",
       "\n",
       "       GFdays  ZRZ  ZDB   CNDL  \n",
       "0          17  111   99   4412  \n",
       "1          13   79   70   4423  \n",
       "2          81   49   41   4455  \n",
       "3           1  173  152   4458  \n",
       "4         269  161  134   4474  \n",
       "...       ...  ...  ...    ...  \n",
       "16507      41  499  468  16603  \n",
       "16508      62  568  437  16701  \n",
       "16509      41  549  510  16907  \n",
       "16510      62  626  473  16930  \n",
       "16511      62  688  524  17362  \n",
       "\n",
       "[16512 rows x 14 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 重新用随机森林输出特征相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y= new_data['CNL']\n",
    "X = new_data[[ 'Taici', 'CDJG', 'MRdays', 'MRL', 'DBL', 'Tc', 'NSD', 'JZmilk',\n",
    "       'WHI', 'GFmilk', 'GFdays', 'ZRZ', 'ZDB', 'CNDL', '1features ',\n",
    "       '2features ', '3features ', '4features ', '5features ', '6features ',\n",
    "       '7features ', '8features ', '9features ', '10features ']]\n",
    "# # -*- coding: utf-8 -*-\n",
    "# from sklearn.ensemble import RandomForestRegressor\n",
    "# import numpy as np\n",
    " \n",
    "# # load boston housing dataset as an example\n",
    "\n",
    "# names=new_data.columns\n",
    "# rf = RandomForestRegressor()\n",
    "# rf.fit(X,Y)\n",
    "# print(\"Features sorted by their score:\")\n",
    "# print(sorted(zip(map(lambda x:round(x,4),rf.feature_importances_),names),reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 交叉验证递归特征消除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\environment\\Anaconda3\\envs\\tf2\\lib\\site-packages\\sklearn\\base.py:446: UserWarning: X does not have valid feature names, but RFECV was fitted with feature names\n",
      "  \"X does not have valid feature names, but\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimal number of features : 19\n",
      "Best features : Index(['Taici', 'MRdays', 'MRL', 'JZmilk', 'GFmilk', 'GFdays', 'ZRZ', 'ZDB',\n",
      "       'CNDL', '1features ', '2features ', '3features ', '4features ',\n",
      "       '5features ', '6features ', '7features ', '8features ', '9features ',\n",
      "       '10features '],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.feature_selection import RFECV\n",
    "\n",
    "#交叉验证递归特征消除\n",
    "clf_rf_4 = RandomForestRegressor() \n",
    "rfecv = RFECV(estimator=clf_rf_4, step=1, cv=5,scoring='neg_mean_squared_error')   #5折交叉验证\n",
    "rfecv = rfecv.fit(X, Y)\n",
    "\n",
    "print('Optimal number of features :', rfecv.n_features_)\n",
    "print('Best features :', X.columns[rfecv.support_])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data.to_csv('特征生成数据集_迭代次数_2.csv',index=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 减小进化的迭代次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    |   Population Average    |             Best Individual              |\n",
      "---- ------------------------- ------------------------------------------ ----------\n",
      " Gen   Length          Fitness   Length          Fitness      OOB Fitness  Time Left\n",
      "   0    12.88         0.188032        9         0.607422         0.594545      0.00s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "SymbolicTransformer(function_set=['add', 'sub', 'mul', 'div', 'log', 'sqrt',\n",
       "                                  'abs', 'neg', 'max', 'min'],\n",
       "                    generations=1, max_samples=0.9, n_jobs=3,\n",
       "                    parsimony_coefficient=0.0005, random_state=0, verbose=1)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gplearn.genetic import SymbolicTransformer \n",
    "import gplearn as gp\n",
    "function_set = ['add', 'sub', 'mul', 'div', 'log', 'sqrt', 'abs', 'neg', 'max', 'min']\n",
    "# generations : 整数，可选(默认值=20)要进化的代数。\n",
    "gp2 = SymbolicTransformer(generations=1, population_size=1000,\n",
    "                         hall_of_fame=100, n_components=10,\n",
    "                         function_set=function_set,\n",
    "                         parsimony_coefficient=0.0005,\n",
    "                         max_samples=0.9, verbose=1,\n",
    "                         random_state=0, n_jobs=3)\n",
    "gp2.fit(X, Y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>GFmilk</th>\n",
       "      <th>...</th>\n",
       "      <th>1features</th>\n",
       "      <th>2features</th>\n",
       "      <th>3features</th>\n",
       "      <th>4features</th>\n",
       "      <th>5features</th>\n",
       "      <th>6features</th>\n",
       "      <th>7features</th>\n",
       "      <th>8features</th>\n",
       "      <th>9features</th>\n",
       "      <th>10features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>345</td>\n",
       "      <td>169</td>\n",
       "      <td>3.39</td>\n",
       "      <td>3.01</td>\n",
       "      <td>67.4</td>\n",
       "      <td>10.74</td>\n",
       "      <td>37.8</td>\n",
       "      <td>89.6</td>\n",
       "      <td>45.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.161149</td>\n",
       "      <td>32.511786</td>\n",
       "      <td>1659.193811</td>\n",
       "      <td>2.911070</td>\n",
       "      <td>1841.607342</td>\n",
       "      <td>2.088766</td>\n",
       "      <td>21.117167</td>\n",
       "      <td>3.602207</td>\n",
       "      <td>12.171126</td>\n",
       "      <td>0.454443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>443</td>\n",
       "      <td>254</td>\n",
       "      <td>3.24</td>\n",
       "      <td>3.12</td>\n",
       "      <td>23.6</td>\n",
       "      <td>11.53</td>\n",
       "      <td>30.3</td>\n",
       "      <td>72.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.554976</td>\n",
       "      <td>23.283023</td>\n",
       "      <td>1504.077354</td>\n",
       "      <td>0.328158</td>\n",
       "      <td>852.429660</td>\n",
       "      <td>0.068938</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.763461</td>\n",
       "      <td>8.417570</td>\n",
       "      <td>-0.259071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>300</td>\n",
       "      <td>81</td>\n",
       "      <td>3.30</td>\n",
       "      <td>2.97</td>\n",
       "      <td>22.3</td>\n",
       "      <td>11.72</td>\n",
       "      <td>21.1</td>\n",
       "      <td>52.7</td>\n",
       "      <td>25.8</td>\n",
       "      <td>...</td>\n",
       "      <td>4.748414</td>\n",
       "      <td>27.261172</td>\n",
       "      <td>639.743861</td>\n",
       "      <td>1.411114</td>\n",
       "      <td>566.622670</td>\n",
       "      <td>0.762915</td>\n",
       "      <td>9.025033</td>\n",
       "      <td>2.338115</td>\n",
       "      <td>10.262768</td>\n",
       "      <td>-0.183613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>288</td>\n",
       "      <td>275</td>\n",
       "      <td>5.47</td>\n",
       "      <td>4.59</td>\n",
       "      <td>23.5</td>\n",
       "      <td>19.43</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.506809</td>\n",
       "      <td>3.207604</td>\n",
       "      <td>85.299673</td>\n",
       "      <td>0.028227</td>\n",
       "      <td>-109.061598</td>\n",
       "      <td>1.585816</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>0.528980</td>\n",
       "      <td>14.065523</td>\n",
       "      <td>-0.040565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>512</td>\n",
       "      <td>269</td>\n",
       "      <td>4.18</td>\n",
       "      <td>3.34</td>\n",
       "      <td>2.9</td>\n",
       "      <td>16.77</td>\n",
       "      <td>39.5</td>\n",
       "      <td>100.3</td>\n",
       "      <td>29.2</td>\n",
       "      <td>...</td>\n",
       "      <td>5.910516</td>\n",
       "      <td>36.142584</td>\n",
       "      <td>819.468791</td>\n",
       "      <td>2.244615</td>\n",
       "      <td>946.310554</td>\n",
       "      <td>1.185729</td>\n",
       "      <td>8.428339</td>\n",
       "      <td>3.252697</td>\n",
       "      <td>10.476573</td>\n",
       "      <td>-0.213705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16507</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>251</td>\n",
       "      <td>3.97</td>\n",
       "      <td>3.17</td>\n",
       "      <td>141.9</td>\n",
       "      <td>11.63</td>\n",
       "      <td>55.6</td>\n",
       "      <td>139.2</td>\n",
       "      <td>67.1</td>\n",
       "      <td>...</td>\n",
       "      <td>9.553306</td>\n",
       "      <td>45.314492</td>\n",
       "      <td>2388.108479</td>\n",
       "      <td>6.770024</td>\n",
       "      <td>3376.057074</td>\n",
       "      <td>6.533289</td>\n",
       "      <td>294.054175</td>\n",
       "      <td>5.137168</td>\n",
       "      <td>13.785437</td>\n",
       "      <td>4.382327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16508</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>214</td>\n",
       "      <td>4.51</td>\n",
       "      <td>2.78</td>\n",
       "      <td>12.1</td>\n",
       "      <td>12.38</td>\n",
       "      <td>74.3</td>\n",
       "      <td>176.3</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.378887</td>\n",
       "      <td>61.861955</td>\n",
       "      <td>2745.751993</td>\n",
       "      <td>7.880234</td>\n",
       "      <td>5164.149595</td>\n",
       "      <td>8.464727</td>\n",
       "      <td>353.970761</td>\n",
       "      <td>5.901875</td>\n",
       "      <td>16.996253</td>\n",
       "      <td>5.710459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16509</th>\n",
       "      <td>2</td>\n",
       "      <td>478</td>\n",
       "      <td>286</td>\n",
       "      <td>3.80</td>\n",
       "      <td>3.50</td>\n",
       "      <td>7.1</td>\n",
       "      <td>15.46</td>\n",
       "      <td>45.9</td>\n",
       "      <td>114.6</td>\n",
       "      <td>67.1</td>\n",
       "      <td>...</td>\n",
       "      <td>7.260333</td>\n",
       "      <td>39.277032</td>\n",
       "      <td>1893.161399</td>\n",
       "      <td>5.830397</td>\n",
       "      <td>1810.207950</td>\n",
       "      <td>5.069086</td>\n",
       "      <td>208.210911</td>\n",
       "      <td>4.461927</td>\n",
       "      <td>11.745263</td>\n",
       "      <td>3.393268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16510</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>239</td>\n",
       "      <td>4.53</td>\n",
       "      <td>2.85</td>\n",
       "      <td>9.2</td>\n",
       "      <td>12.98</td>\n",
       "      <td>66.8</td>\n",
       "      <td>167.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11.657085</td>\n",
       "      <td>57.396811</td>\n",
       "      <td>2570.499706</td>\n",
       "      <td>7.430134</td>\n",
       "      <td>4262.089055</td>\n",
       "      <td>7.380603</td>\n",
       "      <td>318.770213</td>\n",
       "      <td>5.627049</td>\n",
       "      <td>15.528797</td>\n",
       "      <td>5.142878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16511</th>\n",
       "      <td>2</td>\n",
       "      <td>492</td>\n",
       "      <td>274</td>\n",
       "      <td>3.30</td>\n",
       "      <td>3.64</td>\n",
       "      <td>138.2</td>\n",
       "      <td>14.06</td>\n",
       "      <td>57.7</td>\n",
       "      <td>144.2</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>10.228786</td>\n",
       "      <td>48.555553</td>\n",
       "      <td>2208.631564</td>\n",
       "      <td>7.032217</td>\n",
       "      <td>3082.591240</td>\n",
       "      <td>6.483870</td>\n",
       "      <td>261.711512</td>\n",
       "      <td>5.158134</td>\n",
       "      <td>14.378978</td>\n",
       "      <td>4.221153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Taici  CDJG  MRdays   MRL   DBL     Tc    NSD  JZmilk    WHI  GFmilk  \\\n",
       "0          6   345     169  3.39  3.01   67.4  10.74    37.8   89.6    45.0   \n",
       "1          1   443     254  3.24  3.12   23.6  11.53    30.3   72.0    45.0   \n",
       "2          1   300      81  3.30  2.97   22.3  11.72    21.1   52.7    25.8   \n",
       "3          3   288     275  5.47  4.59   23.5  19.43     3.4    8.5    25.6   \n",
       "4          5   512     269  4.18  3.34    2.9  16.77    39.5  100.3    29.2   \n",
       "...      ...   ...     ...   ...   ...    ...    ...     ...    ...     ...   \n",
       "16507      2   478     251  3.97  3.17  141.9  11.63    55.6  139.2    67.1   \n",
       "16508      2   492     214  4.51  2.78   12.1  12.38    74.3  176.3    62.0   \n",
       "16509      2   478     286  3.80  3.50    7.1  15.46    45.9  114.6    67.1   \n",
       "16510      2   492     239  4.53  2.85    9.2  12.98    66.8  167.2    62.0   \n",
       "16511      2   492     274  3.30  3.64  138.2  14.06    57.7  144.2    62.0   \n",
       "\n",
       "       ...  1features   2features    3features   4features    5features   \\\n",
       "0      ...    7.161149   32.511786  1659.193811    2.911070  1841.607342   \n",
       "1      ...    3.554976   23.283023  1504.077354    0.328158   852.429660   \n",
       "2      ...    4.748414   27.261172   639.743861    1.411114   566.622670   \n",
       "3      ...   -4.506809    3.207604    85.299673    0.028227  -109.061598   \n",
       "4      ...    5.910516   36.142584   819.468791    2.244615   946.310554   \n",
       "...    ...         ...         ...          ...         ...          ...   \n",
       "16507  ...    9.553306   45.314492  2388.108479    6.770024  3376.057074   \n",
       "16508  ...   13.378887   61.861955  2745.751993    7.880234  5164.149595   \n",
       "16509  ...    7.260333   39.277032  1893.161399    5.830397  1810.207950   \n",
       "16510  ...   11.657085   57.396811  2570.499706    7.430134  4262.089055   \n",
       "16511  ...   10.228786   48.555553  2208.631564    7.032217  3082.591240   \n",
       "\n",
       "       6features   7features   8features   9features   10features   \n",
       "0        2.088766   21.117167    3.602207   12.171126     0.454443  \n",
       "1        0.068938   72.000000    0.763461    8.417570    -0.259071  \n",
       "2        0.762915    9.025033    2.338115   10.262768    -0.183613  \n",
       "3        1.585816    8.500000    0.528980   14.065523    -0.040565  \n",
       "4        1.185729    8.428339    3.252697   10.476573    -0.213705  \n",
       "...           ...         ...         ...         ...          ...  \n",
       "16507    6.533289  294.054175    5.137168   13.785437     4.382327  \n",
       "16508    8.464727  353.970761    5.901875   16.996253     5.710459  \n",
       "16509    5.069086  208.210911    4.461927   11.745263     3.393268  \n",
       "16510    7.380603  318.770213    5.627049   15.528797     5.142878  \n",
       "16511    6.483870  261.711512    5.158134   14.378978     4.221153  \n",
       "\n",
       "[16512 rows x 24 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "gp_train_feature = gp2.transform(X)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_feature_name = [str(i)+'V' for i in range(1, 11)]\n",
    "train_new_feature = pd.DataFrame(gp_train_feature, columns=new_feature_name, index=X.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_0 = pd.concat([X, train_new_feature], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = pd.concat([Y, x_train_0], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CNL</th>\n",
       "      <th>Taici</th>\n",
       "      <th>CDJG</th>\n",
       "      <th>MRdays</th>\n",
       "      <th>MRL</th>\n",
       "      <th>DBL</th>\n",
       "      <th>Tc</th>\n",
       "      <th>NSD</th>\n",
       "      <th>JZmilk</th>\n",
       "      <th>WHI</th>\n",
       "      <th>...</th>\n",
       "      <th>1V</th>\n",
       "      <th>2V</th>\n",
       "      <th>3V</th>\n",
       "      <th>4V</th>\n",
       "      <th>5V</th>\n",
       "      <th>6V</th>\n",
       "      <th>7V</th>\n",
       "      <th>8V</th>\n",
       "      <th>9V</th>\n",
       "      <th>10V</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CNL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100312</td>\n",
       "      <td>0.023118</td>\n",
       "      <td>-0.346579</td>\n",
       "      <td>-0.099501</td>\n",
       "      <td>-0.235943</td>\n",
       "      <td>-0.050199</td>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.538804</td>\n",
       "      <td>0.534154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.606105</td>\n",
       "      <td>-0.600128</td>\n",
       "      <td>0.545028</td>\n",
       "      <td>0.591231</td>\n",
       "      <td>0.588874</td>\n",
       "      <td>-0.578001</td>\n",
       "      <td>0.577580</td>\n",
       "      <td>0.560868</td>\n",
       "      <td>0.538937</td>\n",
       "      <td>0.535277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taici</th>\n",
       "      <td>0.100312</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.121883</td>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.015819</td>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.056267</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014140</td>\n",
       "      <td>-0.178179</td>\n",
       "      <td>0.000928</td>\n",
       "      <td>-0.080286</td>\n",
       "      <td>-0.078206</td>\n",
       "      <td>-0.257227</td>\n",
       "      <td>0.004763</td>\n",
       "      <td>-0.045432</td>\n",
       "      <td>0.149834</td>\n",
       "      <td>0.016865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CDJG</th>\n",
       "      <td>0.023118</td>\n",
       "      <td>0.121883</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061277</td>\n",
       "      <td>-0.091764</td>\n",
       "      <td>0.037260</td>\n",
       "      <td>0.028510</td>\n",
       "      <td>0.017457</td>\n",
       "      <td>-0.084874</td>\n",
       "      <td>-0.056719</td>\n",
       "      <td>0.030056</td>\n",
       "      <td>0.021762</td>\n",
       "      <td>0.494696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRdays</th>\n",
       "      <td>-0.346579</td>\n",
       "      <td>-0.022526</td>\n",
       "      <td>0.067016</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>...</td>\n",
       "      <td>0.436942</td>\n",
       "      <td>-0.306727</td>\n",
       "      <td>0.250076</td>\n",
       "      <td>0.189065</td>\n",
       "      <td>-0.028034</td>\n",
       "      <td>-0.196812</td>\n",
       "      <td>-0.947574</td>\n",
       "      <td>0.234934</td>\n",
       "      <td>-0.041495</td>\n",
       "      <td>0.324747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRL</th>\n",
       "      <td>-0.099501</td>\n",
       "      <td>0.015819</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.060074</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.218040</td>\n",
       "      <td>-0.148412</td>\n",
       "      <td>-0.288781</td>\n",
       "      <td>0.278832</td>\n",
       "      <td>0.276321</td>\n",
       "      <td>0.036789</td>\n",
       "      <td>0.035101</td>\n",
       "      <td>0.097877</td>\n",
       "      <td>-0.025831</td>\n",
       "      <td>0.098516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBL</th>\n",
       "      <td>-0.235943</td>\n",
       "      <td>-0.017366</td>\n",
       "      <td>0.013370</td>\n",
       "      <td>0.351659</td>\n",
       "      <td>0.331627</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141824</td>\n",
       "      <td>-0.078379</td>\n",
       "      <td>-0.061007</td>\n",
       "      <td>0.082797</td>\n",
       "      <td>0.032545</td>\n",
       "      <td>0.012350</td>\n",
       "      <td>-0.328391</td>\n",
       "      <td>-0.088385</td>\n",
       "      <td>0.033734</td>\n",
       "      <td>-0.099837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tc</th>\n",
       "      <td>-0.050199</td>\n",
       "      <td>0.062100</td>\n",
       "      <td>0.007021</td>\n",
       "      <td>0.054744</td>\n",
       "      <td>0.050499</td>\n",
       "      <td>0.071991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000632</td>\n",
       "      <td>-0.007684</td>\n",
       "      <td>-0.029342</td>\n",
       "      <td>-0.012464</td>\n",
       "      <td>-0.009654</td>\n",
       "      <td>0.007925</td>\n",
       "      <td>-0.059483</td>\n",
       "      <td>-0.027708</td>\n",
       "      <td>-0.013810</td>\n",
       "      <td>-0.004618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NSD</th>\n",
       "      <td>-0.038608</td>\n",
       "      <td>0.011543</td>\n",
       "      <td>-0.008376</td>\n",
       "      <td>0.077701</td>\n",
       "      <td>0.156565</td>\n",
       "      <td>0.172289</td>\n",
       "      <td>-0.012315</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>...</td>\n",
       "      <td>0.112683</td>\n",
       "      <td>-0.098220</td>\n",
       "      <td>0.009050</td>\n",
       "      <td>0.074932</td>\n",
       "      <td>0.066793</td>\n",
       "      <td>-0.074204</td>\n",
       "      <td>-0.045720</td>\n",
       "      <td>0.033069</td>\n",
       "      <td>0.018224</td>\n",
       "      <td>0.030332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JZmilk</th>\n",
       "      <td>0.538804</td>\n",
       "      <td>-0.056267</td>\n",
       "      <td>0.048543</td>\n",
       "      <td>0.462403</td>\n",
       "      <td>0.279166</td>\n",
       "      <td>0.169783</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.080992</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.947513</td>\n",
       "      <td>-0.781217</td>\n",
       "      <td>0.581611</td>\n",
       "      <td>0.844047</td>\n",
       "      <td>0.681838</td>\n",
       "      <td>-0.504148</td>\n",
       "      <td>-0.156757</td>\n",
       "      <td>0.695845</td>\n",
       "      <td>0.354307</td>\n",
       "      <td>0.803898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHI</th>\n",
       "      <td>0.534154</td>\n",
       "      <td>-0.056445</td>\n",
       "      <td>0.049589</td>\n",
       "      <td>0.458415</td>\n",
       "      <td>0.283492</td>\n",
       "      <td>0.174645</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>0.113240</td>\n",
       "      <td>0.994654</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.951381</td>\n",
       "      <td>-0.783452</td>\n",
       "      <td>0.582915</td>\n",
       "      <td>0.851577</td>\n",
       "      <td>0.691492</td>\n",
       "      <td>-0.503761</td>\n",
       "      <td>-0.150399</td>\n",
       "      <td>0.692318</td>\n",
       "      <td>0.352201</td>\n",
       "      <td>0.807377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFmilk</th>\n",
       "      <td>0.507088</td>\n",
       "      <td>0.280424</td>\n",
       "      <td>0.089426</td>\n",
       "      <td>0.215548</td>\n",
       "      <td>-0.047060</td>\n",
       "      <td>-0.006727</td>\n",
       "      <td>0.000330</td>\n",
       "      <td>0.071629</td>\n",
       "      <td>0.437067</td>\n",
       "      <td>0.436352</td>\n",
       "      <td>...</td>\n",
       "      <td>0.656220</td>\n",
       "      <td>-0.806147</td>\n",
       "      <td>0.465184</td>\n",
       "      <td>0.320350</td>\n",
       "      <td>0.204442</td>\n",
       "      <td>-0.955766</td>\n",
       "      <td>-0.082889</td>\n",
       "      <td>0.448083</td>\n",
       "      <td>0.624433</td>\n",
       "      <td>0.424514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFdays</th>\n",
       "      <td>0.016834</td>\n",
       "      <td>-0.081822</td>\n",
       "      <td>0.031838</td>\n",
       "      <td>0.383514</td>\n",
       "      <td>-0.030282</td>\n",
       "      <td>0.120347</td>\n",
       "      <td>-0.005849</td>\n",
       "      <td>0.043313</td>\n",
       "      <td>0.332836</td>\n",
       "      <td>0.326414</td>\n",
       "      <td>...</td>\n",
       "      <td>0.296758</td>\n",
       "      <td>-0.140253</td>\n",
       "      <td>0.242407</td>\n",
       "      <td>0.235891</td>\n",
       "      <td>0.075072</td>\n",
       "      <td>-0.032078</td>\n",
       "      <td>-0.309260</td>\n",
       "      <td>0.225569</td>\n",
       "      <td>-0.039380</td>\n",
       "      <td>0.257603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZRZ</th>\n",
       "      <td>-0.157010</td>\n",
       "      <td>0.066566</td>\n",
       "      <td>0.079993</td>\n",
       "      <td>0.891524</td>\n",
       "      <td>0.079832</td>\n",
       "      <td>0.325674</td>\n",
       "      <td>0.049062</td>\n",
       "      <td>0.064460</td>\n",
       "      <td>0.553473</td>\n",
       "      <td>0.546543</td>\n",
       "      <td>...</td>\n",
       "      <td>0.560564</td>\n",
       "      <td>-0.495334</td>\n",
       "      <td>0.323387</td>\n",
       "      <td>0.241842</td>\n",
       "      <td>0.007460</td>\n",
       "      <td>-0.388028</td>\n",
       "      <td>-0.795221</td>\n",
       "      <td>0.326733</td>\n",
       "      <td>0.277183</td>\n",
       "      <td>0.410966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZDB</th>\n",
       "      <td>-0.165822</td>\n",
       "      <td>0.057212</td>\n",
       "      <td>0.073868</td>\n",
       "      <td>0.909352</td>\n",
       "      <td>0.045137</td>\n",
       "      <td>0.338406</td>\n",
       "      <td>0.049674</td>\n",
       "      <td>0.070040</td>\n",
       "      <td>0.548936</td>\n",
       "      <td>0.542943</td>\n",
       "      <td>...</td>\n",
       "      <td>0.554170</td>\n",
       "      <td>-0.487116</td>\n",
       "      <td>0.330837</td>\n",
       "      <td>0.243973</td>\n",
       "      <td>0.010416</td>\n",
       "      <td>-0.380947</td>\n",
       "      <td>-0.816348</td>\n",
       "      <td>0.317435</td>\n",
       "      <td>0.274689</td>\n",
       "      <td>0.404482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNDL</th>\n",
       "      <td>0.254626</td>\n",
       "      <td>-0.047904</td>\n",
       "      <td>0.058497</td>\n",
       "      <td>0.138192</td>\n",
       "      <td>-0.015833</td>\n",
       "      <td>0.032051</td>\n",
       "      <td>-0.001881</td>\n",
       "      <td>0.012148</td>\n",
       "      <td>0.327275</td>\n",
       "      <td>0.320392</td>\n",
       "      <td>...</td>\n",
       "      <td>0.365490</td>\n",
       "      <td>-0.483377</td>\n",
       "      <td>0.203741</td>\n",
       "      <td>0.215557</td>\n",
       "      <td>0.192635</td>\n",
       "      <td>-0.427458</td>\n",
       "      <td>-0.038531</td>\n",
       "      <td>0.202094</td>\n",
       "      <td>0.413862</td>\n",
       "      <td>0.287192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1V</th>\n",
       "      <td>0.606105</td>\n",
       "      <td>0.014140</td>\n",
       "      <td>0.061277</td>\n",
       "      <td>0.436942</td>\n",
       "      <td>0.218040</td>\n",
       "      <td>0.141824</td>\n",
       "      <td>-0.000632</td>\n",
       "      <td>0.112683</td>\n",
       "      <td>0.947513</td>\n",
       "      <td>0.951381</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.848927</td>\n",
       "      <td>0.677296</td>\n",
       "      <td>0.792433</td>\n",
       "      <td>0.630645</td>\n",
       "      <td>-0.709299</td>\n",
       "      <td>-0.143993</td>\n",
       "      <td>0.773970</td>\n",
       "      <td>0.505230</td>\n",
       "      <td>0.787271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2V</th>\n",
       "      <td>-0.600128</td>\n",
       "      <td>-0.178179</td>\n",
       "      <td>-0.091764</td>\n",
       "      <td>-0.306727</td>\n",
       "      <td>-0.148412</td>\n",
       "      <td>-0.078379</td>\n",
       "      <td>-0.007684</td>\n",
       "      <td>-0.098220</td>\n",
       "      <td>-0.781217</td>\n",
       "      <td>-0.783452</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.848927</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.488005</td>\n",
       "      <td>-0.646964</td>\n",
       "      <td>-0.511315</td>\n",
       "      <td>0.829323</td>\n",
       "      <td>0.059520</td>\n",
       "      <td>-0.540954</td>\n",
       "      <td>-0.499578</td>\n",
       "      <td>-0.684985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3V</th>\n",
       "      <td>0.545028</td>\n",
       "      <td>0.000928</td>\n",
       "      <td>0.037260</td>\n",
       "      <td>0.250076</td>\n",
       "      <td>-0.288781</td>\n",
       "      <td>-0.061007</td>\n",
       "      <td>-0.029342</td>\n",
       "      <td>0.009050</td>\n",
       "      <td>0.581611</td>\n",
       "      <td>0.582915</td>\n",
       "      <td>...</td>\n",
       "      <td>0.677296</td>\n",
       "      <td>-0.488005</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.471425</td>\n",
       "      <td>0.376716</td>\n",
       "      <td>-0.549965</td>\n",
       "      <td>-0.068602</td>\n",
       "      <td>0.751203</td>\n",
       "      <td>0.434821</td>\n",
       "      <td>0.541863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4V</th>\n",
       "      <td>0.591231</td>\n",
       "      <td>-0.080286</td>\n",
       "      <td>0.028510</td>\n",
       "      <td>0.189065</td>\n",
       "      <td>0.278832</td>\n",
       "      <td>0.082797</td>\n",
       "      <td>-0.012464</td>\n",
       "      <td>0.074932</td>\n",
       "      <td>0.844047</td>\n",
       "      <td>0.851577</td>\n",
       "      <td>...</td>\n",
       "      <td>0.792433</td>\n",
       "      <td>-0.646964</td>\n",
       "      <td>0.471425</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.710427</td>\n",
       "      <td>-0.372551</td>\n",
       "      <td>0.095860</td>\n",
       "      <td>0.570444</td>\n",
       "      <td>0.267996</td>\n",
       "      <td>0.697186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5V</th>\n",
       "      <td>0.588874</td>\n",
       "      <td>-0.078206</td>\n",
       "      <td>0.017457</td>\n",
       "      <td>-0.028034</td>\n",
       "      <td>0.276321</td>\n",
       "      <td>0.032545</td>\n",
       "      <td>-0.009654</td>\n",
       "      <td>0.066793</td>\n",
       "      <td>0.681838</td>\n",
       "      <td>0.691492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.630645</td>\n",
       "      <td>-0.511315</td>\n",
       "      <td>0.376716</td>\n",
       "      <td>0.710427</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.282023</td>\n",
       "      <td>0.279803</td>\n",
       "      <td>0.418301</td>\n",
       "      <td>0.206234</td>\n",
       "      <td>0.581393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6V</th>\n",
       "      <td>-0.578001</td>\n",
       "      <td>-0.257227</td>\n",
       "      <td>-0.084874</td>\n",
       "      <td>-0.196812</td>\n",
       "      <td>0.036789</td>\n",
       "      <td>0.012350</td>\n",
       "      <td>0.007925</td>\n",
       "      <td>-0.074204</td>\n",
       "      <td>-0.504148</td>\n",
       "      <td>-0.503761</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.709299</td>\n",
       "      <td>0.829323</td>\n",
       "      <td>-0.549965</td>\n",
       "      <td>-0.372551</td>\n",
       "      <td>-0.282023</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.037810</td>\n",
       "      <td>-0.573166</td>\n",
       "      <td>-0.628474</td>\n",
       "      <td>-0.479624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7V</th>\n",
       "      <td>0.577580</td>\n",
       "      <td>0.004763</td>\n",
       "      <td>-0.056719</td>\n",
       "      <td>-0.947574</td>\n",
       "      <td>0.035101</td>\n",
       "      <td>-0.328391</td>\n",
       "      <td>-0.059483</td>\n",
       "      <td>-0.045720</td>\n",
       "      <td>-0.156757</td>\n",
       "      <td>-0.150399</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.143993</td>\n",
       "      <td>0.059520</td>\n",
       "      <td>-0.068602</td>\n",
       "      <td>0.095860</td>\n",
       "      <td>0.279803</td>\n",
       "      <td>0.037810</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012423</td>\n",
       "      <td>0.172789</td>\n",
       "      <td>-0.070963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8V</th>\n",
       "      <td>0.560868</td>\n",
       "      <td>-0.045432</td>\n",
       "      <td>0.030056</td>\n",
       "      <td>0.234934</td>\n",
       "      <td>0.097877</td>\n",
       "      <td>-0.088385</td>\n",
       "      <td>-0.027708</td>\n",
       "      <td>0.033069</td>\n",
       "      <td>0.695845</td>\n",
       "      <td>0.692318</td>\n",
       "      <td>...</td>\n",
       "      <td>0.773970</td>\n",
       "      <td>-0.540954</td>\n",
       "      <td>0.751203</td>\n",
       "      <td>0.570444</td>\n",
       "      <td>0.418301</td>\n",
       "      <td>-0.573166</td>\n",
       "      <td>-0.012423</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.424085</td>\n",
       "      <td>0.604775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9V</th>\n",
       "      <td>0.538937</td>\n",
       "      <td>0.149834</td>\n",
       "      <td>0.021762</td>\n",
       "      <td>-0.041495</td>\n",
       "      <td>-0.025831</td>\n",
       "      <td>0.033734</td>\n",
       "      <td>-0.013810</td>\n",
       "      <td>0.018224</td>\n",
       "      <td>0.354307</td>\n",
       "      <td>0.352201</td>\n",
       "      <td>...</td>\n",
       "      <td>0.505230</td>\n",
       "      <td>-0.499578</td>\n",
       "      <td>0.434821</td>\n",
       "      <td>0.267996</td>\n",
       "      <td>0.206234</td>\n",
       "      <td>-0.628474</td>\n",
       "      <td>0.172789</td>\n",
       "      <td>0.424085</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.313449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10V</th>\n",
       "      <td>0.535277</td>\n",
       "      <td>0.016865</td>\n",
       "      <td>0.494696</td>\n",
       "      <td>0.324747</td>\n",
       "      <td>0.098516</td>\n",
       "      <td>-0.099837</td>\n",
       "      <td>-0.004618</td>\n",
       "      <td>0.030332</td>\n",
       "      <td>0.803898</td>\n",
       "      <td>0.807377</td>\n",
       "      <td>...</td>\n",
       "      <td>0.787271</td>\n",
       "      <td>-0.684985</td>\n",
       "      <td>0.541863</td>\n",
       "      <td>0.697186</td>\n",
       "      <td>0.581393</td>\n",
       "      <td>-0.479624</td>\n",
       "      <td>-0.070963</td>\n",
       "      <td>0.604775</td>\n",
       "      <td>0.313449</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             CNL     Taici      CDJG    MRdays       MRL       DBL        Tc  \\\n",
       "CNL     1.000000  0.100312  0.023118 -0.346579 -0.099501 -0.235943 -0.050199   \n",
       "Taici   0.100312  1.000000  0.121883 -0.022526  0.015819 -0.017366  0.062100   \n",
       "CDJG    0.023118  0.121883  1.000000  0.067016  0.005464  0.013370  0.007021   \n",
       "MRdays -0.346579 -0.022526  0.067016  1.000000  0.060074  0.351659  0.054744   \n",
       "MRL    -0.099501  0.015819  0.005464  0.060074  1.000000  0.331627  0.050499   \n",
       "DBL    -0.235943 -0.017366  0.013370  0.351659  0.331627  1.000000  0.071991   \n",
       "Tc     -0.050199  0.062100  0.007021  0.054744  0.050499  0.071991  1.000000   \n",
       "NSD    -0.038608  0.011543 -0.008376  0.077701  0.156565  0.172289 -0.012315   \n",
       "JZmilk  0.538804 -0.056267  0.048543  0.462403  0.279166  0.169783  0.004237   \n",
       "WHI     0.534154 -0.056445  0.049589  0.458415  0.283492  0.174645  0.003931   \n",
       "GFmilk  0.507088  0.280424  0.089426  0.215548 -0.047060 -0.006727  0.000330   \n",
       "GFdays  0.016834 -0.081822  0.031838  0.383514 -0.030282  0.120347 -0.005849   \n",
       "ZRZ    -0.157010  0.066566  0.079993  0.891524  0.079832  0.325674  0.049062   \n",
       "ZDB    -0.165822  0.057212  0.073868  0.909352  0.045137  0.338406  0.049674   \n",
       "CNDL    0.254626 -0.047904  0.058497  0.138192 -0.015833  0.032051 -0.001881   \n",
       "1V      0.606105  0.014140  0.061277  0.436942  0.218040  0.141824 -0.000632   \n",
       "2V     -0.600128 -0.178179 -0.091764 -0.306727 -0.148412 -0.078379 -0.007684   \n",
       "3V      0.545028  0.000928  0.037260  0.250076 -0.288781 -0.061007 -0.029342   \n",
       "4V      0.591231 -0.080286  0.028510  0.189065  0.278832  0.082797 -0.012464   \n",
       "5V      0.588874 -0.078206  0.017457 -0.028034  0.276321  0.032545 -0.009654   \n",
       "6V     -0.578001 -0.257227 -0.084874 -0.196812  0.036789  0.012350  0.007925   \n",
       "7V      0.577580  0.004763 -0.056719 -0.947574  0.035101 -0.328391 -0.059483   \n",
       "8V      0.560868 -0.045432  0.030056  0.234934  0.097877 -0.088385 -0.027708   \n",
       "9V      0.538937  0.149834  0.021762 -0.041495 -0.025831  0.033734 -0.013810   \n",
       "10V     0.535277  0.016865  0.494696  0.324747  0.098516 -0.099837 -0.004618   \n",
       "\n",
       "             NSD    JZmilk       WHI  ...        1V        2V        3V  \\\n",
       "CNL    -0.038608  0.538804  0.534154  ...  0.606105 -0.600128  0.545028   \n",
       "Taici   0.011543 -0.056267 -0.056445  ...  0.014140 -0.178179  0.000928   \n",
       "CDJG   -0.008376  0.048543  0.049589  ...  0.061277 -0.091764  0.037260   \n",
       "MRdays  0.077701  0.462403  0.458415  ...  0.436942 -0.306727  0.250076   \n",
       "MRL     0.156565  0.279166  0.283492  ...  0.218040 -0.148412 -0.288781   \n",
       "DBL     0.172289  0.169783  0.174645  ...  0.141824 -0.078379 -0.061007   \n",
       "Tc     -0.012315  0.004237  0.003931  ... -0.000632 -0.007684 -0.029342   \n",
       "NSD     1.000000  0.080992  0.113240  ...  0.112683 -0.098220  0.009050   \n",
       "JZmilk  0.080992  1.000000  0.994654  ...  0.947513 -0.781217  0.581611   \n",
       "WHI     0.113240  0.994654  1.000000  ...  0.951381 -0.783452  0.582915   \n",
       "GFmilk  0.071629  0.437067  0.436352  ...  0.656220 -0.806147  0.465184   \n",
       "GFdays  0.043313  0.332836  0.326414  ...  0.296758 -0.140253  0.242407   \n",
       "ZRZ     0.064460  0.553473  0.546543  ...  0.560564 -0.495334  0.323387   \n",
       "ZDB     0.070040  0.548936  0.542943  ...  0.554170 -0.487116  0.330837   \n",
       "CNDL    0.012148  0.327275  0.320392  ...  0.365490 -0.483377  0.203741   \n",
       "1V      0.112683  0.947513  0.951381  ...  1.000000 -0.848927  0.677296   \n",
       "2V     -0.098220 -0.781217 -0.783452  ... -0.848927  1.000000 -0.488005   \n",
       "3V      0.009050  0.581611  0.582915  ...  0.677296 -0.488005  1.000000   \n",
       "4V      0.074932  0.844047  0.851577  ...  0.792433 -0.646964  0.471425   \n",
       "5V      0.066793  0.681838  0.691492  ...  0.630645 -0.511315  0.376716   \n",
       "6V     -0.074204 -0.504148 -0.503761  ... -0.709299  0.829323 -0.549965   \n",
       "7V     -0.045720 -0.156757 -0.150399  ... -0.143993  0.059520 -0.068602   \n",
       "8V      0.033069  0.695845  0.692318  ...  0.773970 -0.540954  0.751203   \n",
       "9V      0.018224  0.354307  0.352201  ...  0.505230 -0.499578  0.434821   \n",
       "10V     0.030332  0.803898  0.807377  ...  0.787271 -0.684985  0.541863   \n",
       "\n",
       "              4V        5V        6V        7V        8V        9V       10V  \n",
       "CNL     0.591231  0.588874 -0.578001  0.577580  0.560868  0.538937  0.535277  \n",
       "Taici  -0.080286 -0.078206 -0.257227  0.004763 -0.045432  0.149834  0.016865  \n",
       "CDJG    0.028510  0.017457 -0.084874 -0.056719  0.030056  0.021762  0.494696  \n",
       "MRdays  0.189065 -0.028034 -0.196812 -0.947574  0.234934 -0.041495  0.324747  \n",
       "MRL     0.278832  0.276321  0.036789  0.035101  0.097877 -0.025831  0.098516  \n",
       "DBL     0.082797  0.032545  0.012350 -0.328391 -0.088385  0.033734 -0.099837  \n",
       "Tc     -0.012464 -0.009654  0.007925 -0.059483 -0.027708 -0.013810 -0.004618  \n",
       "NSD     0.074932  0.066793 -0.074204 -0.045720  0.033069  0.018224  0.030332  \n",
       "JZmilk  0.844047  0.681838 -0.504148 -0.156757  0.695845  0.354307  0.803898  \n",
       "WHI     0.851577  0.691492 -0.503761 -0.150399  0.692318  0.352201  0.807377  \n",
       "GFmilk  0.320350  0.204442 -0.955766 -0.082889  0.448083  0.624433  0.424514  \n",
       "GFdays  0.235891  0.075072 -0.032078 -0.309260  0.225569 -0.039380  0.257603  \n",
       "ZRZ     0.241842  0.007460 -0.388028 -0.795221  0.326733  0.277183  0.410966  \n",
       "ZDB     0.243973  0.010416 -0.380947 -0.816348  0.317435  0.274689  0.404482  \n",
       "CNDL    0.215557  0.192635 -0.427458 -0.038531  0.202094  0.413862  0.287192  \n",
       "1V      0.792433  0.630645 -0.709299 -0.143993  0.773970  0.505230  0.787271  \n",
       "2V     -0.646964 -0.511315  0.829323  0.059520 -0.540954 -0.499578 -0.684985  \n",
       "3V      0.471425  0.376716 -0.549965 -0.068602  0.751203  0.434821  0.541863  \n",
       "4V      1.000000  0.710427 -0.372551  0.095860  0.570444  0.267996  0.697186  \n",
       "5V      0.710427  1.000000 -0.282023  0.279803  0.418301  0.206234  0.581393  \n",
       "6V     -0.372551 -0.282023  1.000000  0.037810 -0.573166 -0.628474 -0.479624  \n",
       "7V      0.095860  0.279803  0.037810  1.000000 -0.012423  0.172789 -0.070963  \n",
       "8V      0.570444  0.418301 -0.573166 -0.012423  1.000000  0.424085  0.604775  \n",
       "9V      0.267996  0.206234 -0.628474  0.172789  0.424085  1.000000  0.313449  \n",
       "10V     0.697186  0.581393 -0.479624 -0.070963  0.604775  0.313449  1.000000  \n",
       "\n",
       "[25 rows x 25 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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